Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

Chi, Yuanying; Bai, Guoqing; Gao, Kaiye; Peng, Rui

doi:10.1109/access.2021.3127909

Cited by 5 publications

(3 citation statements)

References 46 publications

(58 reference statements)

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“…Huang et al [68] proposed an evaluation index to effectively evaluate the health condition of the battery of an energy-storage device and verified the validity of the evaluation index. Cheng et al [69] provided an algorithm for the reliability assessment of a battery storage system considering the life degradation of lithium-ion batteries, which is a reliability assessment algorithm based on the generalized generating function [70][71][72][73][74][75]. Liu et al [76] study the reliability problem of battery storage systems composed of battery modules and introduced a reliability assessment method for battery modules based on a generalized generating function, as: Define the UGF Expression for the Battery Cell…”

Section: Reliability Assessment Of Eessmentioning

confidence: 99%

A Comprehensive Review of Key Technologies for Enhancing the Reliability of Lithium-Ion Power Batteries

Ren,

Jin,

Fang

et al. 2023

Energies

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Fossil fuel usage has a great impact on the environment and global climate. Promoting new energy vehicles (NEVs) is essential for green and low-carbon transportation and supporting sustainable development. Lithium-ion power batteries (LIPBs) are crucial energy-storage components in NEVs, directly influencing their performance and safety. Therefore, exploring LIPB reliability technologies has become a vital research area. This paper aims to comprehensively summarize the progress in LIPB reliability research. First, we analyze existing reliability studies on LIPB components and common estimation methods. Second, we review the state-estimation methods used for accurate battery monitoring. Third, we summarize the commonly used optimization methods in fault diagnosis and lifetime prediction. Fourth, we conduct a bibliometric analysis. Finally, we identify potential challenges for future LIPB research. Through our literature review, we find that: (1) model-based and data-driven approaches are currently more commonly used in state-estimation methods; (2) neural networks and deep learning are the most prevalent methods in fault diagnosis and lifetime prediction; (3) bibliometric analysis indicates a high interest in LIPB reliability technology in China compared to other countries; (4) this research needs further development in overall system reliability, research on real-world usage scenarios, and advanced simulation and modeling techniques.

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Section: Reliability Assessment Of Eessmentioning

confidence: 99%

A Comprehensive Review of Key Technologies for Enhancing the Reliability of Lithium-Ion Power Batteries

Ren,

Jin,

Fang

et al. 2023

Energies

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“…The appointment scheduling system is a potentially useful tool for reducing health management costs and maximizing medical benefits. Improving system reliability and cost savings are the main ideas of optimization [101][102][103][104]. Profit maximization is becoming a major research objective due to the need for cost efficiency and facing budget cuts.…”

Section: Economic Performancementioning

confidence: 99%

A Review of Optimization Studies for System Appointment Scheduling

Niu,

Lei,

Guo

et al. 2023

Axioms

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In the face of an increasingly high-demand environment for outpatients, achieving a balance between allocation of limited medical resources and patient satisfaction has considerable social and economic benefits. Therefore, appointment scheduling (AS) system operation is used in clinics and hospitals, and its operation optimization research is of great significance. This study reviews the research progress on appointment scheduling system optimization. Firstly, we classify and conclude the existing appointment scheduling system structures and decision-making frameworks. Subsequently, we summarize the system reliability optimization framework from three aspects: appointment scheduling system optimization objectives, decision variables and constraints. Following that, we methodically review the most applied system optimization algorithms in different appointment scheduling systems. Lastly, a literature bibliometric analysis is provided. During our review of the literature, we observe that (1) optimization methods in ASs predominantly involve the application of genetic algorithms and simulation optimization algorithms; (2) neural networks and deep learning methods are core technologies in health management optimization; (3) a bibliometric analysis reveals a heightened interest in the optimization technology of ASs within China compared to other nations; and (4) further advancements are essential in the comprehensive optimization of the system, exploration of practical usage scenarios, and the application of advanced simulation and modeling techniques in this research.

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“…In traditional binary reliability/availability studies, a system or component is typically assumed to have two states: completely working or totally failed. However, complex systems in the real-world, such as power systems, communication systems, and production systems [1], [2], [3] etc., often present multiple states during operation, and different states have different performance rates, which are called multi-state system (MSS). As a more flexible and accurate tool for complex system analysis, the MSS model has been widely studied, because it can characterize the multi-state deteriorating nature of complex systems [4].…”

Section: Introductionmentioning

confidence: 99%

Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements

Li,

Xue,

Wang

et al. 2023

IEEE Access

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As an important aspect of reliability theory, availability has now been considered a very meaningful design criterion of repairable system. This paper investigates the availability evaluation and design optimization of the multi-state k-out-of-n: G system considering random weight threshold. The system availability is evaluated by extending the recursive algorithm (RA) and universal generating function (UGF) technique. Based on the traditional recursive algorithm, the total probability theorem is used to solve the discrete random weight threshold. Another better UGF method combines a new stochastic joint operator, which is suitable for both continuous and discrete random weight thresholds. Furthermore, we constructed two system design optimization models under availability or cost constraint respectively, and genetic algorithm (GA) programming can be applied to obtain the optimal state probability distribution and weight distribution of multi-state components of the suggested system. Finally, through numerical examples, the flexibility and effectiveness of the proposed methods for design optimization are demonstrated. In addition, two evaluation methods are compared to show that the customized UGF method features higher generality than RA in the case of continuous stochastic weight threshold, and higher operational efficiency in the case of increasing component quantity and state. The results can be helpful for engineers to optimize the design of complex systems.

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Reliability Evaluation of Multi-State Systems With Common Bus Performance Sharing Considering Performance Excess

Cited by 5 publications

References 46 publications

A Comprehensive Review of Key Technologies for Enhancing the Reliability of Lithium-Ion Power Batteries

A Comprehensive Review of Key Technologies for Enhancing the Reliability of Lithium-Ion Power Batteries

A Review of Optimization Studies for System Appointment Scheduling

Availability Evaluation and Design Optimization of Multi-State k-out-of-n: G Systems With Random Performance Requirements

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