Challenges and opportunities for battery health estimation:Bridging laboratory research and real-world applications

Addressing climate change demands a significant shift away from fossil fuels,with sectors like electricity and transportation relying heavily on renewable energy.Integral to this transition are energy storage systems,notably lithium-ion batteries.Over time,these batteries degrade,affecting their efficiency and posing safety risks.Monitoring and predicting battery aging is essential,especially estimating its state of health(SOH).Various SOH estimation methods exist,from traditional model-based approaches to machine learning approaches.

The First China Sports and Health Conference was Held in Beijing

On May 27,2023,the first China Sports and Health Conference was successfully held in Beijing,which was hosted by the Chinese Preventive Medicine Association(CMPA)and organized by the Capital University of Physical Education and Sports(Beijing Institute for International Olympic Studies)and the Sports and Health Branch of the CMPA.

Public satisfaction with the quality of First Health Facility Services in Indonesia: Does sociodemographic matter?

Objective:To investigate individual characteristics related to satisfaction with the quality of First Health Facility Services(FHFS)in Indonesia.Methods:This cross-sectional study analyzes national representation data.Meanwhile,the study involved 9846 representative respondents in 2019.Respondent’s satisfaction with FHFS based on the five dimensions of service quality(SERVQUAL)is a dependent variable.Independent variables consist of sex,marital status,age,education,employment,insurance ownership,and economics.The study used multivariate logistic regression to explain the relationship between individual characteristics and FSHS quality.Results:77.3%Respondents were satisfied with FHFS,with the highest order of satisfaction dimensions being assurance(59.4%),empathy(57.3%),reliability(53.6%),responsiveness(52.7%),and then tangibility(49.1%).Multivariate logistic analysis showed that divorce was 1.48 more likely than never-married to be satisfied(95%CI 1.17-1.87).Employees were 0.77 less likely than the unemployed to get satisfied(95%CI 0.70-0.86).Respondents with higher education was 0.82 less likely than those with primary education to be satisfied(95%CI 0.67-0.99).Meanwhile,respondents who had government-run insurance were 1.61 more likely than uninsured to be satisfied(95%CI 1.42-1.80).Moreover,the rich were 0.82 less likely than the poor to get satisfied(95%CI 0.73-0.92).Conclusions:Community satisfaction with FHFS is generally high,though some areas could be improved.Demographic factors are still strongly related to satisfaction ratings.The government can assess the quality of services in accordance with standards and disseminate information about service standards for primary facilities to all levels of society,ensuring that service satisfaction is rated as good by all groups.

全健康(One Health)视角下绿色健康社区景观设计体系构建

以全健康(OneHealth)视角为出发点,保障人、环境和动物的健康对于社区健康环境规划与设计具有重要意义。在现有健康社区景观设计体系中,人、环境、物种三者关系虽被提及,但未被系统探究,健康社区建设实践也需要系统性的景观设计体系支持。基于全健康理念中人、环境和物种的相互关系,结合生态系统服务功能、康复景观理论和园艺疗法,进一步探讨人、环境、物种健康之间的关联途径。通过对全健康理念视角下的3个层次进行演绎发展,归纳总结了人的健康、环境健康和物种健康的组成要素及内容,构建了以人的健康需求为导向的社区健康设计框架,提出了以人与人际、人与环境和人与物种为三大圈层的健康社区景观设计体系。全健康视角为社区健康环境设计提供了一个系统性、整合性且具有操作性的框架,未来应重视健康社区体系中各类疗愈空间的设计与使用,以增进社区居民共享的健康福祉。

COVID-19 Pandemic Impact on Mental Health in First Year Secondary School Students

Confinement was a helpful measure to avoid virus propagation, but social isolation and the massive closure of face-to face activities in educational institutions, impacted negatively in mental health of students, it increased stress and anxiety in adolescents, affecting their communication skills in this significant step of interpersonal relationships, and the search for their identity. The lockdown in addition to stress and anxiety triggered fear emotions, frustration, worrying and anger, as well as changes in driving energy, diminishing interest and desires. This work aimed to analyze the impact on mental health in first year secondary school adolescents after the COVID-19 pandemic lockdown. Method: Qualitative and phenomenological research, 25 students of first year from a public secondary school of Mexico’s metropolitan area participated in the study;they were girls and boys 12 - 13 years old. Data collection was through a semi-structured interview, testimonials and anecdotes, in two hour sessions, along a week;research team recorded the interviews, testimonials and anecdotes. A signed informed consent was obtained from school authorities, parents and the assent of students. Obtained qualitative data were analyzed according to De Souza Minayo. Results: Four categories emerged with sub-categories. Category 1: Anxiety crisis, sub-categories 1.1. In overcrowded places, 1.2. To speak in public, 1.3. Facing interpersonal relationships with peers. Category 2: Impaired self-concept, sub-categories 2.1. Deficient self-perception, 2.2 Continuous disqualification and 2.3. Deficient personal objectivity. Category 3: Emotions handling, and sub-categories 3.1 Deficient identification of emotions, 3.2 Deficient handling of emotions, 3.3 Maximized emotions. Category 4: Coping strategies, and sub-categories 4.1 Deficient coping strategies, 4.2 Self-injuries, 4.3 Solitude. Conclusion: In early adolescence and in the post-pandemic context tools to face them are insufficient to develop social skills and coping strategies. Lockdown interrupted their socialization process, and their relationships with peers made them anxious and led them to risk behaviors. In this context alternatives to develop significant learning are needed, based on adolescents’ self-awareness highlighting adaptation, communication, emotional intelligence, creative problem solving and resilience skills.

Alexa,let's train now!——A systematic review and classification approach to digital and home-based physical training interventions aiming to support healthy cognitive aging

Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.

Health Systems Strengthening to Tackle the Global Burden of Pediatric and Congenital Heart Disease: A Diagonal Approach

1 Background Congenital heart disease(CHD)is the most common major congenital anomaly,affecting approximately one in every 100 live births[1].Among congenital anomalies,66%of preventable deaths are due to CHD,and 58%of the avertable morbidity and mortality due to congenital anomalies would result from scaling congenital heart surgery services[2].Every year,nearly 300,000 children and adults die from CHD,the majority of whom live in low-and middle-income countries(LMICs)[3].Approximately 49%of all individuals with CHD will require surgical or interventional care at some point in their lifetime[4];as a result of advances in access to and the delivery of such services,over 95%of children born with CHD in high-income countries now live into adulthood[3].Here,adults have surpassed children in the number of CHD cases at a ratio of 2:1[5].

Probiotic cocktails accelerate baicalin metabolism in the ileum to modulate intestinal health in broiler chickens

Background Baicalin and probiotic cocktails are promising feed additives with broad application prospects.While probiotic cocktails are known to enhance intestinal health,the potential synergistic impact of combining baicalin with probiotic cocktails on the gut health of broiler chickens remains largely unexplored.Therefore,this study aims to investigate the influence of the combined administration of baicalin and probiotic cocktails on the composition of ileal and cecal microbiota in broiler chickens to elucidate the underlying mechanisms responsible for the healthpromoting effects.Results A total of 3201-day-old male Arbor Acres broilers were divided into 4 groups,each with 8 replicates of 10 chicks per replicate.Over a period of 42 d,the birds were fed a basal diet or the same diet supplemented with 37.5 g/t baicalin(BC),1,000 g/t probiotic cocktails(PC),or a combination of both BC(37.5 g/t)and PC(1,000 g/t).The results demonstrated that BC+PC exhibited positive synergistic effects,enhancing intestinal morphology,immune function,and barrier function.This was evidenced by increased VH/CD ratio,sIgA levels,and upregulated expression of occludin and claudin-1(P<0.05).16S rRNA analysis indicated that PC potentiated the effects of BC,particularly in the ileum,where BC+PC significantly increased theα-diversity of the ileal microbiota,altered itsβ-diversity,and increased the relative abundance of Flavonifractor(P<0.05),a flavonoid-metabolizing bacterium.Furthermore,Flavonifractor positively correlated with chicken ileum crypt depth(P<0.05).While BC+PC had a limited effect on cecal microbiota structure,the PC group had a very similar microbial composition to BC+PC,suggesting that the effect of PC at the distal end of the gut overshadowed those of BC.Conclusions We demonstrated the synergistic enhancement of gut health regulation in broiler chickens by combining baicalin and probiotic cocktails.Probiotic cocktails enhanced the effects of baicalin and accelerated its metabolism in the ileum,thereby influencing the ileal microbiota structure.This study elucidates the interaction mechanism between probiotic cocktails and plant extract additives within the host microbiota.These findings provide compelling evidence for the future development of feed additive combinations.

Clinical Analysis and Mental Health Survey of Hemophilia Carriers:a Cross-sectional Study

Objective:Hemophilia carriers(HCs),who are heterozygous for mutations in the clotting factor VIII/clotting factor IX gene(F8 or F9),may have a wide range of clotting factor levels,from very low,similar to afflicted males,to the upper limit of normal,and may experience mental health issues.The purpose of this study was to provide genetic information on mothers of hemophilia patients and to understand the clotting factor activity and phenotype of HCs.Additionally,we aimed to investigate the mental health status of HCs in China.Methods:A total of 127 hemophilia mothers,including 93 hemophilia A(HA)mothers and 34 hemophilia B(HB)mothers,were enrolled in this study.Long distance PCR,multiplex PCR,and Sanger sequencing were used to analyze mutations in F8 or F9.Coagulation factor activity was detected by a one-stage clotting assay.The Symptom Checklist 90(SCL-90,China/Mandarin version)was given to HCs at the same time to assess their mental health.Results:A total of 90.6%of hemophilia mothers were diagnosed genetically as carriers,with inversion in intron 22 and missense mutations being the most common mutation types in HA and HB carriers,respectively.The median clotting factor level in carriers was 0.74 IU/mL(ranging from 0.09 to 1.74 IU/mL)compared with 1.49 IU/mL(ranging from 0.93 to 1.89 IU/mL)in noncarriers,of which 14.3%of HCs had clotting factor levels of 0.40 IU/mL or below.A total of 53.8%(7/13)of HA carriers with low clotting factor levels(less than 0.50 IU/mL)had a history of bleeding,while none of the HB carriers displayed a bleeding phenotype.The total mean score and the global severity index of the SCL-90 for surveyed HCs were 171.00(±60.37)and 1.78(±0.59),respectively.A total of 67.7%of the respondents had psychological symptoms,with obsessive-compulsive disorder being the most prevalent and severe.The pooled estimates of all nine factors were significantly higher than those in the general population(P<0.05).Conclusions:The detection rate of gene mutations in hemophilia mothers was 90.6%,with a median clotting factor level of 0.74 IU/mL,and 14.3%of HCs had a clotting factor level of 0.40 IU/mL or below.A history of bleeding was present in 41.2%of HCs with low clotting factor levels(less than 0.50 IU/mL).Additionally,given the fragile mental health status of HCs in China,it is critical to develop efficient strategies to improve psychological well-being.

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

Identifying the Hydrochemical Characteristics,Genetic Mechanisms and Potential Human Health Risks of Fluoride and Nitrate Enriched Groundwater in the Tongzhou District,Beijing,North China

Fluoride and nitrate enriched groundwater are potential threats to the safety of the groundwater supply that may cause significant effects on human health and public safety,especially in aggregated population areas and economic hubs.This study focuses on the high F^(−)and NO_(3)^(−)concentration groundwater in Tongzhou District,Beijing,North China.A total of 36 groundwater samples were collected to analyze the hydrochemical characteristics,elucidate genetic mechanisms and evaluate the potential human health risks.The results of the analysis indicate:Firstly,most of the groundwater samples are characterized by Mg-HCO_(3) and Na-HCO_(3) with the pH ranging from 7.19 to 8.28 and TDS with a large variation across the range 471-2337 mg/L.The NO_(3)^(−)concentration in 38.89%groundwater samples and the F^(−)concentration in 66.67%groundwater samples exceed the permissible limited value.Secondly,F^(−)in groundwater originates predominantly from water-rock interactions and the fluorite dissolution,which is also regulated by cation exchange,competitive adsorption of HCO_(3)−and an alkaline environment.Thirdly,the effect of sewage disposal and agricultural activities have a significant effect on high NO3-concentration,while the high F^(−)concentration is less influenced by anthropogenic activity.The alkaline environment favors nitrification,thus being conducive to the production of NO_(3)^(−).Finally,the health risk assessment is evaluated for different population groups.The results indicate that high NO_(3)^(−)and F^(−)concentration in groundwater would have the largest threat to children’s health.The findings of this study could contribute to the provision of a scientific basis for groundwater supply policy formulation relating to public health in Tongzhou District.

A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

The Access control scheme is an effective method to protect user data privacy.The access control scheme based on blockchain and ciphertext policy attribute encryption(CP–ABE)can solve the problems of single—point of failure and lack of trust in the centralized system.However,it also brings new problems to the health information in the cloud storage environment,such as attribute leakage,low consensus efficiency,complex permission updates,and so on.This paper proposes an access control scheme with fine-grained attribute revocation,keyword search,and traceability of the attribute private key distribution process.Blockchain technology tracks the authorization of attribute private keys.The credit scoring method improves the Raft protocol in consensus efficiency.Besides,the interplanetary file system(IPFS)addresses the capacity deficit of blockchain.Under the premise of hiding policy,the research proposes a fine-grained access control method based on users,user attributes,and file structure.It optimizes the data-sharing mode.At the same time,Proxy Re-Encryption(PRE)technology is used to update the access rights.The proposed scheme proved to be secure.Comparative analysis and experimental results show that the proposed scheme has higher efficiency and more functions.It can meet the needs of medical institutions.

Assessment of groundwater quantity, quality, and associated health risk of the Tano river basin, Ghana

In the Tano River Basin,groundwater serves as a crucial resource;however,its quantity and quality with regard to trace elements and microbiological loadings remain poorly understood due to the lack of groundwater logs and limited water research.This study presents a comprehensive analysis of the Tano River Basin,focusing on three key objectives.First,it investigated the aquifer hydraulic parameters and the results showed significant spatial variations in borehole depths,yields,transmissivity,hydraulic conductivity,and specific capacity.Deeper boreholes were concentrated in the northeastern and southeastern zones,while geological formations,particu-larly the Apollonian Formation,exhibit a strong influence on borehole yields.The study identified areas with high transmissivity and hydraulic conductivity in the southern and eastern regions,suggesting good groundwater avail-ability and suitability for sustainable water supply.Sec-ondly,the research investigated the groundwater quality and observed that the majority of borehole samples fall within WHO(Guidelines for Drinking-water Quality,Environmental Health Criteria,Geneva,2011,2017.http://www.who.int)limit.However,some samples have pH levels below the standards,although the groundwater generally qualifies as freshwater.The study further explores hydrochemical facies and health risk assessment,highlighting the dominance of Ca–HCO3 water type.Trace element analysis reveals minimal health risks from most elements,with chromium(Cr)as the primary contributor to chronic health risk.Overall,this study has provided a key insights into the Tano River Basin’s hydrogeology and associated health risks.The outcome of this research has contributed to the broader understanding of hydrogeologi-cal dynamics and the importance of managing groundwater resources sustainably in complex geological environments.

Exploring Nutritional Compositions,Volatile Compounds,Health Benefits,Emerging Processing Technologies,and Potential Food Products of Glutinous Rice:A Review

Glutinous rice(Oryza sativa var.glutinosa)stands out as one of the most popular rice varieties globally,amidst thousands of rice cultivars.Its increasing popularity is attributed to its rich nutritional compositions and health benefits.This review aims to summarize the nutritional compositions,volatile compounds,and health benefits of glutinous rice.Further,in-depth studies are necessary to explore the utilization of glutinous rice in enhancing processing technologies and developing new food products.Glutinous rice has been shown to possess numerous health benefits,including antioxidant activity,bioactive compounds,anti-cancer properties,anti-inflammatory effects,anti-diabetic potential,and cholesterol-lowering effects.Besides its nutritional compositions,the major volatile compounds identified in glutinous rice could serve as a functional food for human consumption.Emerging processing technologies related to glutinous rice are elaborated to improve the latest developments for incorporating them into various food products.

Energy evolution and structural health monitoring of coal under different failure modes:An experimental study

Structural instability in underground engineering,especially in coal-rock structures,poses significant safety risks.Thus,the development of an accurate monitoring method for the health of coal-rock bodies is crucial.The focus of this work is on understanding energy evolution patterns in coal-rock bodies under complex conditions by using shear,splitting,and uniaxial compression tests.We examine the changes in energy parameters during various loading stages and the effects of various failure modes,resulting in an innovative energy dissipation-based health evaluation technique for coal.Key results show that coal bodies go through transitions between strain hardening and softening mechanisms during loading,indicated by fluctuations in elastic energy and dissipation energy density.For tensile failure,the energy profile of coal shows a pattern of “high dissipation and low accumulation” before peak stress.On the other hand,shear failure is described by “high accumulation and low dissipation” in energy trends.Different failure modes correlate with an accelerated increase in the dissipation energy before destabilization,and a significant positive correlation is present between the energy dissipation rate and the stress state of the coal samples.A novel mathematical and statistical approach is developed,establishing a dissipation energy anomaly index,W,which categorizes the structural health of coal into different danger levels.This method provides a quantitative standard for early warning systems and is adaptable for monitoring structural health in complex underground engineering environments,contributing to the development of structural health monitoring technology.

美国《保健物理》(Health Physics)杂志英文摘要(2023年126卷第2期)

Statistical Analysis of Radioactivity:Lamprecht Uranium Mine in Texas Mark C.Harvey1 and Nancy L.Glenn Griesinger2(1.Department of Physics,Texas Southern University,Houston,TX 77004;2.Department of Mathematical Sciences,Texas Southern University,Houston,TX 77004)Abstract:The former Lamprecht uranium mine facility in Texas ceased operations well before the new millennium.However,decommissioning activities were never completed by the licensee.Consequently,a legal proceeding was authorized between state and licensee representatives.Meanwhile,state funds were used to hire an independent contractor to perform radiological surveys and assess the magnitude of residual radioactivity across the terrain at the site.The purpose of this study was to apply advanced spatial statistical methods to the survey data measured by contractors at the Lamprecht site to precisely predict remaining radioactive hotspot locations post soil remediation activities.

Gut microbiota and female health

The gut microbiota is recognized as an endocrine organ with the capacity to influence distant organs and associated biological pathways.Recent advan-cements underscore the critical role of gut microbial homeostasis in female health;with dysbiosis potentially leading to diseases among women such as polycystic ovarian syndrome,endometriosis,breast cancer,cervical cancer,and ovarian cancer etc.Despite this,there has been limited discussion on the underlying mechanisms.This editorial explores the three potential mechanisms through which gut microbiota dysbiosis may impact the development of diseases among women,namely,the immune system,the gut microbiota-estrogen axis,and the metabolite pathway.We focused on approaches for treating diseases in women by addressing gut microbiota imbalances through probiotics,prebiotics supple-mentation,and fecal microbiota transplantation(FMT).Future studies should focus on determining the molecular mechanisms underlying associations between dysbiosis of gut microbiota and female diseases to realize precision medicine,with FMT emerging as a promising intervention.

Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.

Rapid health estimation of in-service battery packs based on limited labels and domain adaptation

For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery packs.However,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical scenarios.To address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this paper.First,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inconsistency degrees.Then,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery health.Furthermore,data-driven models based on deep convolutional neural network(DCNN)are constructed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model adaptability.Finally,field data of 10 EVs exhibiting different SOHs are used to verify the proposed methods.By using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.

Research on Condenser Deterioration Evolution Trend Based on ANP-EWM Fusion Health Degree

This study presents a proposed method for assessing the condition and predicting the future status of condensers operating in seawater over an extended period.The aim is to address the problems of scaling and corrosion,which lead to increased loss of cold resources.The method involves utilising a set of multivariate feature parameters associated with the condenser as input for evaluation and trend prediction.This methodology offers a precise means of determining the optimal timing for condenser cleaning,with the ultimate goal of improving its overall performance.The proposed approach involves the integration of the analytic network process with subjective expert experience and the entropy weightmethod with objective big data analysis to develop a fusion health degreemodel.The mathematical model is constructed quantitatively using the improved Mahalanobis distance.Furthermore,a comprehensive prediction model is developed by integrating the improved Informer model and Markov error correction.This model takes into account the health status of the equipment and several influencing factors,includingmultivariate feature characteristics.This model facilitates the objective examination and prediction of the progression of equipment deterioration trends.The present study involves the computation and verification of the field time series data,which serves to demonstrate the accuracy of the condenser health-related models proposed in this research.These models effectively depict the real condition and temporal variations of the equipment,thus offering a valuable method for determining the precise cleaning time required for the condenser.