scholarly journals Life Prediction of Battery Using a Neural Gaussian Process with Early Discharge Characteristics

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1087
Author(s):  
Aijun Yin ◽  
Zhibin Tan ◽  
Jian Tan
Keyword(s):  
Life Cycle ◽  
Gaussian Process ◽  
Early Discharge ◽  
Remaining Useful Life ◽  
Operating Conditions ◽  
Cycle Life ◽  
Normal Operation ◽  
Discharge Characteristics ◽  
Whole Life Cycle ◽  
Capacity Prediction

The state of health (SOH) prediction of lithium-ion batteries (LIBs) is of crucial importance for the normal operation of the battery system. In this paper, a new method for cycle life and full life cycle capacity prediction is proposed, which combines the early discharge characteristics with the neural Gaussian process (NGP) model. The cycle data sets of commercial LiFePO4(LFP)/graphite cells generated under different operating conditions are analyzed, and the power characteristic P is extracted from the voltage and current curves of the early cycles. A Pearson correlation analysis shows that there is a strong correlation between P and cycle life. Our model achieves 8.8% test error for predicting cycle life using degradation data for the 20th to 110th cycles. Based on the predicted cycle life, capacity degradation curves for the whole life cycle of the cells are predicted. In addition, the NGP method, combined with power characteristics, is compared with other classical methods for predicting the remaining useful life (RUL) of LIBs. The results demonstrate that the proposed prediction method of cycle life and capacity has better battery life and capacity prediction. This work highlights the use of early discharge characteristics to predict battery performance, and shows the application prospect in accelerating the development of electrode materials and optimizing battery management systems (BMS).

Similarity-based information fusion grey model for remaining useful life prediction of aircraft engines

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaoyu Yang ◽  
Zhigeng Fang ◽  
Xiaochuan Li ◽  
Yingjie Yang ◽  
David Mba
Keyword(s):  
Life Cycle ◽  
Information Fusion ◽  
Remaining Useful Life ◽  
Grey Model ◽  
Aircraft Engines ◽  
Content Type ◽  
Useful Life ◽  
Whole Life Cycle ◽  
Historical Samples

PurposeOnline health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing technologies. The purpose of this paper is to construct a more accurate and stable grey model based on similar information fusion to predict the real-time remaining useful life (RUL) of aircraft engines.Design/methodology/approachFirst, a referential database is created by applying multiple linear regressions on historical samples. Then similarity matching is conducted between the monitored engine and historical samples. After that, an information fusion grey model is applied to predict the future degradation trajectory of the monitored engine considering the latest trend of monitored sensory data and long-term trends of several similar referential samples, and the real-time RUL is obtained correspondingly.FindingsThe results of comparative analysis reveal that the proposed model, which is called similarity-based information fusion grey model (SIFGM), could provide better RUL prediction from the early degradation stage. Furthermore, SIFGM is still able to predict system failures relatively accurately when only partial information of the referential samples is available, making the method a viable choice when the historical whole life cycle data are scarce.Research limitations/implicationsThe prediction of SIFGM method is based on a single monotonically changing health indicator (HI) synthesized from monitoring sensory signals, which is assumed to be highly relevant to the degradation processes of the engine.Practical implicationsThe SIFGM can be used to predict the degradation trajectories and RULs of those online condition monitoring systems with similar irreversible degradation behaviors before failure occurs, such as aircraft engines and centrifugal pumps.Originality/valueThis paper introduces the similarity information into traditional GM(1,1) model to make it more suitable for long-term RUL prediction and also provide a solution of similarity-based RUL prediction with limited historical whole life cycle data.

scholarly journals USING OF THE MATHEMATICAL APPARATUS REGRESSION ANALYSIS TO UNIFY THE CALCULATING METHODOLOGY FOR THE T-64B TANK'S OVERHAUL LIFE

2021 ◽  
Vol 5 (3) ◽  
pp. 151-157
Author(s):  
Helen Makogon ◽  
Volodymyr Chalapko ◽  
Serhiy Guba ◽  
Vladyslav Staryshenko ◽  
Viktor Moskalenko ◽  
...  
Keyword(s):  
Life Cycle ◽  
Service Life ◽  
Training Group ◽  
Regression Equation ◽  
Operating Conditions ◽  
Analytical Dependence ◽  
Normal Operation ◽  
Mathematical Apparatus ◽  
Repair Service ◽  
Combat Training

The subject matter of the article is the life cycle of a T-64B tank sample during the period from normal operation in a combat training group to resource consumption and carrying out average and capital repairs. The goal of the study is to develop a model of dependence of inter-repair service life of the T-64B tank sample on the machine operating conditions and, on its basis, a methodology for controlling the parameters of individual assemblies and systems of the tank sample during its life cycle. The tasks to be solved are: to analyze the results of statistical records of tank system failures and damages number and identify the predicates set affect the inter-repair service life of the machine depending on conditions of its tasks for the intended purposes; to create the regression equation for getting the unified analytical dependence of inter-repair service life of the T-64B tank sample in the period from normal operation in training and combat group to service life and overhaul; to investigate specific influence of reliability indices on the machine's service life. General scientific and special methods of scientific knowledge are used. The method of hierarchy analysis, mathematical apparatus of probability theory and multidimensional statistical analysis were used. The following results are obtained. A set of predicates influence the inter-repair service life of the machine depending on conditions of its tasks for the intended purposes fulfillment has been determined. A regression equation has been drawn up to obtain a unified analytical dependence of the overhaul life of a T-64B tank sample during the period from normal operation in a combat training group to the development of a resource and carrying out of intermediate and complete overhauls were drawn up. Engineering solutions have been proposed to implement a methodology for monitoring the parameters of individual units and systems of the tank sample during its life cycle, namely integrated real-time monitoring of oil condition and recording of engine operating hours under various load conditions. Conclusions. The space of features characterizes the conditions of the tank sample tasks for its intended purposes, includes service life, crew training, operation, seasonality of the unit’s performed tasks nature, machine  operating time since the last service and range of the vehicle before the next overhaul. The analytical relationship between the individual factors determining the conditions under which the T-64B tank sample performs its tasks for the intended purposes and the machine's service life consumption as a dependent variable can be determined in the form of a regression equation. Differentiated control of the parameters of individual assembly units and systems of the tank sample plays a leading role in ensuring the combat readiness and efficiency of the use of aging samples of weapons, insures personnel against possible accidents and catastrophes, sudden failures.

Effects of Pavement Condition on LCCA User Costs

2019 ◽  
Vol 2673 (5) ◽  
pp. 339-350 ◽  
Author(s):  
Egemen Okte ◽  
Imad L. Al-Qadi ◽  
Hasan Ozer
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
The United States ◽  
Operating Conditions ◽  
Work Zone ◽  
Operating Costs ◽  
Normal Operation ◽  
Normal Operating ◽  
User Costs

Life cycle cost analysis (LCCA) is one of the well-established methods to determine the cost-effective alternative between different transportation infrastructure projects. Life cycle cost of a roadway alternative consists of agency and user costs over an analysis period appropriately selected. Agency costs include initial construction costs, and maintenance and rehabilitation costs incurred within the analysis period. User costs incur when there is a work zone present and also during normal operating conditions. In traditional LCCA, adopted by many agencies around the United States, it is assumed that the difference in user cost between alternatives mainly arise from work zone costs. The costs that arise during normal operating conditions (mainly vehicle operating costs) are not dependent on project alternatives and thus are traditionally considered to be negligible. This paper introduces a methodology to test the sensitivity of vehicle operating costs to roughness and texture profile quantitatively and evaluate its contribution to LCCA calculations. It was hypothesized that even the slight changes in surface profile between various alternatives may result in different user costs between the alternatives. A case study is presented to illustrate the effect of user costs of normal operating conditions on LCCA analysis results. Case study showed that vehicle operating costs that arise during normal operation may greatly affect the results of LCCA and should be considered, especially for low-volume traffic projects.

scholarly journals Construction of exchange integrated information chain management model leading by information nurse for large instrument and equipment in operating room

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jinghua Dai ◽  
Xiaoqiang Ren ◽  
Peng Wu ◽  
Xiangdong Wang ◽  
Jiang Li ◽  
...  
Keyword(s):  
Life Cycle ◽  
Life Cycle Management ◽  
Management Model ◽  
Control Group ◽  
Equipment Management ◽  
Observation Group ◽  
Chain Management ◽  
Information Chain ◽  
Whole Life Cycle ◽  
Running Mode

Abstract Background This study aims to explore the information chain management model of large instrument and equipment inter-working in the operating room (OR) led by information nurses. Methods Through the chain management process of large instruments and equipment in the OR, which was based on information nurses, the management model of inter-working and integrating information chain was established, the key links were controlled, and the whole life cycle management of instruments and equipment from expected procurement to scrapping treatment was realized. Using the cluster sampling method, 1562 surgical patients were selected. Among these patients, 749 patients were assigned to the control group before the running mode, and 813 patients were assigned to the observation group after the running mode. The related indexes for large instrument and equipment management in the department before and after the running mode were compared. Results In the observation group, the average time of equipment registration was (22.05 ± 2.36), the cost was reduced by 2220 yuan/year, and the satisfaction rate of the nursing staff was 97.62%. These were significantly better, when compared to the control group (P < 0.05). Furthermore, the awareness rate of the whole staff for equipment repair application was 95.12%, and the arrival time of maintenance personnel and the examination and approval time of equipment management were greatly shortened (P < 0.05). Conclusion The integrated management model of large instrument and equipment interworking in the OR based on chain flow realizes the whole life cycle management of instruments and equipment, which is essential to improve management efficiency.

scholarly journals BIM-Based Tools for Managing Construction and Demolition Waste (CDW): A Scoping Review

2021 ◽  
Vol 13 (15) ◽  
pp. 8427
Author(s):  
Bahareh Nikmehr ◽  
M. Reza Hosseini ◽  
Jun Wang ◽  
Nicholas Chileshe ◽  
Raufdeen Rameezdeen
Keyword(s):  
Life Cycle ◽  
Scoping Review ◽  
Construction And Demolition Waste ◽  
Future Research ◽  
Demolition Waste ◽  
Scant Attention ◽  
Intellectual Deficiencies ◽  
Whole Life Cycle ◽  
Point Of Reference ◽  
Design And Construction

This article provides a picture of the latest developments in providing BIM-based tools for construction and demolition waste (CDW) management. The coverage and breadth of the literature on offering BIM-based tools and technologies for dealing with CDW throughout the whole life cycle of construction are investigated, and gaps are identified. Findings reveal that, although various BIM-based technologies are closely associated with CDW, much of the existing research on this area has focused on the design and construction phase; indeed, the problem of CDW in post-construction stages has received scant attention. Besides, the now available tools and technologies are lacking in cross-phase insights into project waste aspects and are weak in theoretical rigor. This article contributes to the field by identifying the intellectual deficiencies in offering BIM-based tools and technologies when dealing with CDW. So, too, it points to major priorities for future research on the topic. For practitioners, the study provides a point of reference and raises awareness in the field about the most advanced available BIM-based technologies for dealing with CDW problems.

scholarly journals Solid-State Lithium Battery Cycle Life Prediction Using Machine Learning

2021 ◽  
Vol 11 (10) ◽  
pp. 4671
Author(s):  
Danpeng Cheng ◽  
Wuxin Sha ◽  
Linna Wang ◽  
Shun Tang ◽  
Aijun Ma ◽  
...  
Keyword(s):  
Machine Learning ◽  
Solid State ◽  
Life Prediction ◽  
Learning Algorithm ◽  
Remaining Useful Life ◽  
Cycle Life ◽  
Quantitative Prediction ◽  
Test Accuracy ◽  
Machine Learning Algorithm ◽  
Discharge Data

Battery lifetime prediction is a promising direction for the development of next-generation smart energy storage systems. However, complicated degradation mechanisms, different assembly processes, and various operation conditions of the batteries bring tremendous challenges to battery life prediction. In this work, charge/discharge data of 12 solid-state lithium polymer batteries were collected with cycle lives ranging from 71 to 213 cycles. The remaining useful life of these batteries was predicted by using a machine learning algorithm, called symbolic regression. After populations of breed, mutation, and evolution training, the test accuracy of the quantitative prediction of cycle life reached 87.9%. This study shows the great prospect of a data-driven machine learning algorithm in the prediction of solid-state battery lifetimes, and it provides a new approach for the batch classification, echelon utilization, and recycling of batteries.

Innovation and Corporate Social Responsibility in SMEs

2015 ◽  
Vol 808 ◽  
pp. 359-363
Author(s):  
Cristina Feniser ◽  
Florin Lungu
Keyword(s):  
Corporate Social Responsibility ◽  
Life Cycle ◽  
Open Innovation ◽  
Social Goals ◽  
New Approach ◽  
Rational Management ◽  
Corporate Social ◽  
Qualitative Exploration ◽  
Whole Life Cycle ◽  
The Relationship

So far little attention has been given the differences or the compatibilities between CSR and innovation. Few works treats CSR in combination with innovation. What exactly is the relationship between CSR and innovation? Recent phenomena such as open innovation is based on the concept that the stakeholder's dialogue that overlaps with some dimensions of CSR. Being innovative means to bring organizational and technical improvements which will translate into a better position in the market. These improvements don't just aim the product, but the process by which it is obtained and its whole life-cycle. We're talking about a new approach to innovation, namely its orientation towards sustainability. Although SMEs have many features which facilitate implementation of CSR, activities of this type in such organizations are still limited. SMEs managers often make choices that are related to rational management. This leads to divergence between economical and social goals. Through a qualitative exploration of the concepts of CSR and innovation, we wanted to find out from some managers whether there is a link between innovation and CSR in SMEs and whether the activities corresponding to the two concepts overlap in a certain measure.

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