State-of-Health Estimation for Lithium-Ion Batteries Based on the Multi-Island Genetic Algorithm and the Gaussian Process Regression

Wang, Zhenpo; Ma, Jun; Zhang, Lei

doi:10.1109/access.2017.2759094

Cited by 146 publications

(65 citation statements)

References 33 publications

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“…Here, the main objective of using the converter is to supply a specific constant power from the battery to the load by controlling the source current. On the other hand, the converter is much smaller than that used in UC/battery design and the main advantage of this design is the wide power range of UC [11]. This design is advantageous in the sense that there is no variation in the DC link voltage [11]; the major drawback is that it requires a large converter to handle the power of UC.…”

Section: Battery/uc Designmentioning

confidence: 99%

“…On the other hand, the converter is much smaller than that used in UC/battery design and the main advantage of this design is the wide power range of UC [11]. This design is advantageous in the sense that there is no variation in the DC link voltage [11]; the major drawback is that it requires a large converter to handle the power of UC. Hence, it adversely affects the cost and size of the ESS (Energy Storage System).…”

Section: Battery/uc Designmentioning

confidence: 99%

“…Several distinguished authors [8][9][10][11][12] shed light on the research design by considering different objectives with respect to electric vehicles, as outlined below.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, in the study by Wang et al [11], the SOH model was further established on the basis of Gaussian process regression (GPR), in which the optimal hyper parameters were calculated through the conjugate gradient method and the multi-island genetic algorithm (MIGA). The effects of different kernel functions were also analyzed.…”

Section: Introductionmentioning

confidence: 99%

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Battery Life Enhancement in a Hybrid Electrical Energy Storage System Using a Multi-Source Inverter

Mahadik

Vadirajacharya

2019

WEVJ

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This paper introduces a new topology using a multi-source inverter with the intention of reducing the battery current and weight, while enhancing the battery life and increasing the driving range for plug-in electric vehicles, with the combination of a battery and an ultracapacitor (UC) as storage devices. The proposed topology interconnects the UC and battery directly to the three-phase load with a single-stage conversion using an inverter. The battery life is considerably reduced due to excess (peak) current drawn by the load, and these peak load current requirements are met by connecting the ultracapacitor to the battery, controlled through an inverter. Here, the battery is used to cater to the needs of constant profile energy demands, and the UC is used to meet the dynamic peak load profile. This system is highly efficient and cost-effective when compared to a contemporary system with a single power source. Through a comparative analysis, the cost-effectiveness of the proposed energy management system (EMS) is explained in this paper. Energy and power exchange are implemented with an open-loop control strategy using the PSIM simulation environment, and the system is developed with a hardware prototype using different modes of inverter control, which reduces the average battery current to 27% compared to the conventional case. The driving range of electric vehicles is extended using active power exchange between load and the sources. The dynamics of the ultracapacitor gives a quick response, with battery current shared by the ultracapacitor. As a result, the battery current is reduced, thereby enhancing the driving cycle. With the prototype, the results of the proposed topology are validated.

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Section: Battery/uc Designmentioning

confidence: 99%

Section: Battery/uc Designmentioning

confidence: 99%

“…Several distinguished authors [8][9][10][11][12] shed light on the research design by considering different objectives with respect to electric vehicles, as outlined below.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Battery Life Enhancement in a Hybrid Electrical Energy Storage System Using a Multi-Source Inverter

Mahadik

Vadirajacharya

2019

WEVJ

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“…Otherwise, the ICA studies have been validated for on-line SOH estimation for various perspectives such as area, position, and gradient [5,28]. In [29], based on IC curve, feasibility and accuracy of the degradation model is established using Gaussian function. The battery SOH estimation is achieved by analysis the degradation model of capacity.…”

Section: Introductionmentioning

confidence: 99%

State of health estimation for Li-Ion battery using incremental capacity analysis and Gaussian process regression

Yuan

et al. 2020

Energy

Self Cite

251

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Electrolyte Degradation During Aging Process of Lithium‐Ion Batteries: Mechanisms, Characterization, and Quantitative Analysis

Liao,

Zhang,

Peng

et al. 2024

Advanced Energy Materials

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Given that the non‐aqueous electrolyte in Li‐ion battery plays a specific role as an ion‐transport medium and interfacial modifier for both cathode and anode, understanding and evaluating the evolution and degradation of electrolytes throughout the life cycle is a fundamental concern within the lithium‐ion battery (LIB) community. This article provides a comprehensive overview of the electrolyte decomposition processes, mechanisms, effects of electrolyte degradation on the battery performance, characterization techniques, and modeling analysis. First, it thoroughly discusses the processes and mechanisms involved in electrolyte degradation from two primary perspectives: 1) the formation of the electrode‐electrolyte interphase and 2) the decomposition of the bulk electrolyte. Subsequently, it systematically outlines the effects of electrolyte degradation on the battery performance. The article further introduces cutting‐edge characterization and detection techniques used to assess electrolyte degradation, with a specific emphasis on quantitative methods for analyzing residual electrolytes in practical cells. Moreover, it summarizes advanced physical models of electrolyte decomposition. Finally, the paper concludes by offering insights into future trends and potential challenges in battery degradation research, it offers valuable references and guidance for further exploration of electrolyte degradation in LIBs.

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State-of-Health Estimation for Lithium-Ion Batteries Based on the Multi-Island Genetic Algorithm and the Gaussian Process Regression

Cited by 146 publications

References 33 publications

Battery Life Enhancement in a Hybrid Electrical Energy Storage System Using a Multi-Source Inverter

Battery Life Enhancement in a Hybrid Electrical Energy Storage System Using a Multi-Source Inverter

State of health estimation for Li-Ion battery using incremental capacity analysis and Gaussian process regression

Electrolyte Degradation During Aging Process of Lithium‐Ion Batteries: Mechanisms, Characterization, and Quantitative Analysis

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