Satyaprakash Rout, Satyajit Das, K.M. Sanjeeva Kumar
et al.
Lithium-ion batteries, being the core power sources in electric vehicles and energy storage systems, require accurate State-of-Charge (SOC) estimation to ensure optimized performance and extended lifespan. The implementation of accurate SOC estimation algorithms in battery management systems (BMS) not only ensures safety and reliability but also helps in monitoring and mitigating the adverse effects of overcharging and deep discharging. Although numerous review articles have addressed model-based and data-driven SOC estimation techniques, limited attention has been given to battery model parameterization, testing methodologies, and the practical challenges associated with joint and dual model-based estimation frameworks. This review provides a comprehensive discussion of battery testing methods and critically examines the advantages and limitations of various parameterization techniques used in battery modeling. Furthermore, the operational challenges encountered in real-time SOC estimation under dynamic operating conditions are systematically analyzed. Advanced estimation strategies, including joint and dual estimation frameworks, with particular emphasis on adaptive Kalman filter-based approaches, are reviewed for their potential to enhance estimation accuracy, robustness, and adaptability. Finally, a comparative assessment of the reviewed methods is presented, highlighting their suitability for real-time implementation. The insights provided in this review are intended to support researchers and industry practitioners in selecting and developing advanced SOC estimation techniques to improve battery performance and extend operational lifespan.
Winter wheat cultivation faces yield reductions in the North China Plain due to drought and excessive nitrogen fertilizer use, exacerbated by climate change. This study employed a life cycle assessment approach, integrating economic and material input-output data, to evaluate the eco-efficiency of reduced irrigation and nitrogen fertilizer inputs. Field experiments were conducted with four irrigation regimes at the jointing stage (W0: no irrigation; W1: 75 mm), heading stage (W2: additional 75 mm), and filling stage (W3: additional 75 mm), in combination with three nitrogen fertilization levels (conventional, N250: 250 kg ha−1; 20 % reduction, N200: 200 kg ha−1; 40 % reduction, and N150: 150 kg ha−1). The interactive effects on environmental benefits were comprehensively assessed. Results showed irrigation frequency had higher effect on yield than nitrogen application, with nitrogen reduction causing a maximum yield loss of 11.7 %, while reduced irrigation led to 34.0–48.9 % yield losses. Under conditions of sufficient water availability, total environmental costs were inversely correlated with wheat yield and did not increase with higher irrigation frequency. Specifically, increasing irrigation frequency reduced total environmental costs by an average of 32.4 %, 26.9 %, and 23.7 % under N250, N200, and N150 fertilization levels, respectively. Nitrogen fertilizer inputs represented the largest contributor to environmental costs, accounting for 25.6–60.1 % of the total environmental burden. Nitrogen reduction strategies enhanced overall eco-efficiency and lowered environmental costs, whereas water-saving measures involving reduced irrigation decreased eco-efficiency and increased environmental costs. The optimal strategy for high-quality wheat production involved applying 150 kg ha−1 nitrogen and irrigating twice (W2), balancing yield, sustainability, and eco-efficiency. This approach effectively balances yield, environmental sustainability, and eco-efficiency, providing a practical solution to address the environmental challenges of wheat production in the region.
The goal of this research was to examine tail dependence structures between selected commodity futures returns. Tail dependence, called also extremal dependence, was evaluated for the pairs of commodities coming from the same sector (energy or agricultural). The study covers the years 2018-2023, embracing the COVID-19 pandemic and the outbreak of the Russia-Ukraine war. To achieve the goal, bivariate dynamic models were applied to percentage log returns of commodity futures. Marginal distributions were described using the ARMA-GARCH models. Joint distributions were constructed using the symmetrized Joe-Clayton copula, which allowed to model asymmetric dependence in the tails of a distribution. Time variation of the copula parameters, here equal to tail dependence coefficients, was described using the evolution equations [Patton 2006]. In the energy sector, the dependence in both tails of analyzed distributions was relatively strong, dynamic and higher in the lower tail than in the upper tail. On the contrary, the agricultural sector lacks common patterns of tail dependency. This feature of the agricultural sector creates an opportunity for investors or risk managers to build well-diversified portfolios.
Usa Wannasingha Humphries, Muhammad Waqas, Phyo Thandar Hlaing
et al.
Climate change (CC) is causing a significant threat to agriculture, a sector complicatedly tied to natural resources. Changes in precipitation patterns, atmospheric water content, and rising temperatures intensely affect global agriculture, especially in tropical regions. In this intense CC scenario, potential evapotranspiration (PET) and crop water requirement (CWR) are critical components of agricultural water management. This study evaluates the future impact of CC on precipitation, CWR, and PET in different provinces of Thailand's northern and northeastern regions. Three bias correction methods (Delta (DT), Empirical Quantile Mapping (EQM), and Quantile Mapping (QM)) were employed for precipitation downscaling from the CanESM5 CMIP6-GCM across selected 13 coffee farms with different coffee species. Arabica and Robusta coffee were carefully selected for this analysis. The DT method demonstrated superiority, exhibiting lower RMSE and higher correlation coefficients than EQM and QM. Farm-specific assessments illuminated water demand's complex dynamics during critical growth stages, showcasing variable CWR and PET. During the blooming stage in N-F1, CWR ranged from 16.7 to 33.7 mm/stage, highlighting the variability in water needs. Projected CC impacts on Arabica and Robusta coffee farms in Chiang Rai and Sisaket presented challenges, emphasizing farm-specific strategies to address potential water deficits or surpluses during critical growth phases. Projected 2023, 2028, and 2033 precipitation demonstrated incongruities with CWR and PET. The findings emphasize the crucial role of farm-specific adaptive strategies in mitigating the impacts of changing precipitation patterns on coffee cultivation.
Abstract
This study aimed to evaluate the effectiveness of Laney p' chart in overcoming the limitations of conventional p-chart in cigar quality control, especially in handling overdispersion of production data. Overdispersion often occurs in agricultural processes with large sample sizes, resulting in narrow control limits and false alarms. The study was conducted at PT Taru Martani, using cigar quality data from three main production units from August 2021 to July 2022. A quantitative descriptive approach was used to analyze the proportion of product defects. Initial analysis with conventional p-chart showed that 29,140 units in the Cocoon Unit, 23,602 units in the Rolling Unit, and 5,987 units in the Dry Cigar Unit were out of control due to overdispersion. After the Laney p' chart application, the control limits were expanded to 234.7%, significantly reducing false alarms and increasing sensitivity to actual variations in the data. The analysis showed that Laney p' chart was more effective in identifying relevant process variations. The process in the Dry Cigar Unit continued to show instability, likely due to humidity and raw material quality fluctuations. These findings highlight the importance of environmental control and raw material stability in maintaining product quality. This study provided practical contributions to the quality control of high-value agricultural products. It is recommended that further studies explore the integration of other statistical methods and study deeply the relationship between external factors and product quality.
Keywords: Agricultural products, cigars, Laney p' chart, overdispersion, quality control
Abstrak
Penelitian ini bertujuan untuk mengevaluasi efektivitas Laney p' chart dalam mengatasi keterbatasan p-chart konvensional pada pengendalian mutu cerutu, khususnya dalam menangani overdispersi data produksi. Overdispersi sering kali muncul dalam proses agrikultur dengan ukuran sampel besar, menghasilkan batas kendali yang sempit dan alarm palsu. Studi dilakukan di PT Taru Martani, menggunakan data mutu cerutu dari tiga unit produksi utama selama Agustus 2021 hingga Juli 2022. Pendekatan deskriptif kuantitatif digunakan untuk menganalisis proporsi kecacatan produk. Analisis awal dengan p-chart konvensional menunjukkan bahwa 29.140 unit di Unit Kepompong, 23.602 unit di Unit Pelintingan, dan 5.987 unit di Unit Cerutu Kering berada di luar kendali akibat overdispersi. Setelah penerapan Laney p' chart, batas kendali diperluas hingga 234,7%, mengurangi alarm palsu secara signifikan dan meningkatkan sensitivitas terhadap variasi nyata dalam data. Hasil analisis menunjukkan Laney p' chart lebih efektif dalam mengidentifikasi variasi proses yang relevan. Proses di Unit Cerutu Kering, misalnya, tetap menunjukkan ketidakstabilan, kemungkinan akibat fluktuasi kelembaban dan kualitas bahan baku. Temuan ini menyoroti pentingnya pengendalian lingkungan dan stabilitas bahan baku dalam menjaga mutu produk. Penelitian ini memberikan kontribusi praktis dalam pengendalian mutu produk agrikultur bernilai tinggi. Disarankan agar studi lanjutan mengeksplorasi integrasi metode statistik lain dan mempelajari hubungan lebih dalam antara faktor eksternal dengan mutu produk.
Kata kunci: Cerutu, Laney p' chart, overdispersi, pengendalian mutu, produk agrikultur
Vinay Vijayakumar, Yiannis Ampatzidis, John K. Schueller
et al.
In this study, the previous work, present status, benefits, and limitations of the state-of-the-art technologies used in smart spraying technologies in precision weed management are reviewed. A total of 116 articles were identified from Google Scholar and Scopus to study the research work in the field of smart sprayers and precision weed management. The articles were examined based on the relevance, research focus, novelties, measured parameters, used technologies, and field of applications. Smart sprayers based on machine vision (MV) and artificial intelligence (AI) are keys to improving crop productivity and meeting the food demands of the future by reducing the yield losses due to weeds and working towards a sustainable future in agriculture. Many papers published in recent years have focused more on the machine vision, weed detection, and classification aspects of the weeding robot. Very few studies have attempted to discuss the components of a smart weeding machine, non-chemical-based weeders, the components of spraying systems, their controls, underlying fluid mechanics, and the field trials of these weeding robots. This article reviews conventional weeding techniques, machine-vision-based weeding robots, and spraying systems proposed or constructed in the last twenty-five years. Key technologies such as non-chemical-based weeding machines, image preprocessing, feature extraction, and weed detection based on machine learning (ML) and deep learning (DL) for smart sprayers are discussed. The fundamental components of a smart spraying system are also discussed, and previous works are compared to highlight the key components, the spraying accuracy, and the major advantages and disadvantages. The fluid mechanics of the spraying system and its associated controls involved are also presented. There are still many bottlenecks in weed detection systems and smart spraying systems. The results of the systematic review provide an understanding of the progress made in the field of robotic weed detection, herbicide and non-herbicide-based weed management, the use of machine vision, and the limitations of the current spraying systems.
Aqly Tyasna Fiqhry, Tri Nugraha Budi Santoso, Fani Ardiani
Several factors, including the less-than-optimal altitude of Arabica coffee planting influence the low productivity of Arabica coffee in Temanggung Regency. The lack of rejuvenation of production plants means that old coffee plants have low productivity; apart from these two factors, farmers do not have good plant management skills. This research further examines the influence of altitude on Arabica coffee production. This research was carried out in Temanggung Regency, with the sub-districts that were the sample for this research being Ngadirejo District, with an altitude range of 900-1150 m asl, Parakan District, with an altitude range of 1150-1400 m asl, and Kledung District with an altitude range of more than 1400 m asl. The sampling method employed in this study is a purposive sampling technique; the researcher directly determines the location and source of research information. A total of 28 participants responded to this study, with an assessment sample taken of 5% of the population of Arabica coffee plantations that bear fruit. The analysis used the linear regression method of a fixed variable, namely height, and independent variables, namely production, productivity, and evaluation, with a significance level of 5%. The research results show that altitude does influence productivity. If altitude increases, productivity will also increase.
Ammonia (NH3) has gained broad attention as a carbon-free alternative fuel, and its blend with H2 has been especially investigated to mediate the low reactivity of NH3. In the present work, the laminar burning velocities (SL) of NH3+H2+N2+O2 flames were investigated at 1 atm and 298 K, and the oxygen fractions (xO2) in O2+N2 were varied from 0.16 to 0.26, comprising a set of conditions that have not yet been investigated in literature. An updated mechanism was proposed on the basis of our previous published mechanism, which was validated using not only the present data, but also the literature data for NH3 laminar burning velocities and ignition delay times. Over the tested experimental conditions, better predictions were achieved with the updated mechanism. Simulations using the updated and five literature mechanisms were carried out, i.e., mechanisms from Stagni, Bertolino, Shrestha, Konnov, and Mei. The updated and Mei mechanisms reproduce the best the present experimental data. To investigate which reactions influence most the SL increments due to O2 and H2 addition, SL increment parameters were defined for xO2 and xH2 separately. Based on the available experimental data, detailed sensitivity analyses were carried out for these target parameters using the updated and some other mechanisms from the literature. It's found that reactions dominating these parameters could be largely different, thus considerations covering all aspects of SL as well as the SL increment parameters are suggested for the NH3 mechanism validations. Despite the SL increment parameters have different tendencies against the xO2 and xH2 with different reaction sensitivities, local similarities are found if the increments of xO2 and xH2 have been enough refined. Specifically, when the xO2 and xH2 values grow larger, the effects of their increase become well blurred, extending the region of the similar conditions, which is helpful for the determination of inconsistent experimental data.
Fuel, Energy industries. Energy policy. Fuel trade
As a dynamic research method for molecular systems, molecular dynamic (MD) simulation can represent physical phenomena that cannot be realized by experimental means and discuss the microscopic reaction mechanism of things from the molecular level. In this paper, the previous research results were reviewed. First, the MD simulation process was briefly described, then, the applicability of different molecular force fields in the natural gas hydrate (NGH) system was discussed, and finally, the application of MD simulation in the formation and decomposition law of NGH was summarized from the perspective of NGH mining. The results show that the selection of water molecular force field has a great influence on the simulation results, and the evaluation of water model applicable to the simulation of NGH under different thermodynamic states is still an open research field that needs to be paid attention to. The effect of surface properties of porous media (such as crystallinity and hydrophilicity) on hydrate needs to be further studied. Compared with thermodynamic inhibitors, kinetic inhibitors (such as amino acids) have more promising research prospects, and further research can be carried out in the screening of efficient kinetic inhibitors in the future.
Fusarium oxysporum is a pathogen that causes wilt in oil palm and can cause oil palm sprout decay. The study aimed to determine the effectivity of mangosteen peel extract (Garcinia mangostana L.) in inhibiting the growth of Fusarium oxysporum in vitro and in vivo. The research was conducted in November 2017 to June 2018 at the Politeknik Negeri Lampung. The method used was a completely randomized design (CRD) consisting of 5 treatments, namely the concentration of mangosteen peel extract 0% (control), 15%, 30%, 45%,and 60%. Data were analyzed using analysis of variance (ANOVA) and further tests of mean values using the LSD test. The results showed that mangosteen peel extract affected the percentage of inhibitory zone extract in Fusarium oxysporum in vitro at concentrations of 15%, 30%, and 45% respectively at 25,92%, 29,06% and 35,95%. The treatment of mangosteen peel extract also affected the percentage of disease incidence and number of leaves in in vivo testing.
分布式能源的增多进一步推进了电力系统配电侧的演化，而在系统权力逐渐下放的整体趋势下，配电市场的自主化程度也在逐步提升。然而，现有配电侧只能在大规模电网投资的前提下消纳、应用大量分布式能源。因此，需要引入分布式能源市场实现大规模分布式能源的并网，最大化分布式能源的价值。新兴配电侧市场的发展需要更多的配电系统管理以及进一步探究配电系统运营商（distribution system operator, DSO）的功能。现有DSO研究虽较完善地探究了未来DSO功能以及相关的系统管理角色，但大多基于DSO一次性实现其全部功能的前提，未将DSO发展看作一个动态过程，且未对DSO与其他层面管理机构的相互协作做充分研究。基于上述背景，针对配电系统演化进程的三个典型阶段，提出配电层电力市场的演化进程；归纳了未来配电网需要DSO承担的4项管理角色；分析DSO在配电市场自主化进程的不同阶段需扮演的角色及其具体管理任务，同时探究DSO与其他系统管理机构之间的责任划分与合作执行方式。以英国未来配电市场及其运营模式的探究为例，为其他国家与地区的分布式能源市场发展与相应市场监管体系建立提供借鉴。
The research goal of this paper is to identify the possibility to transform the concept of Corporate Social Responsibility (CSR) towards the concept of Creating Shared Value (CSV) in agribusiness. In the paper, both concepts are compared and the ways of their application are exemplified. A literature review and summative content analysis have been used to study CSR reports of four leading food companies in Poland. The study enabled the exemplification of good practices of shared value creation in the analysed agribusiness entities which publish information on their social impact. It concludes that the implementation of a new CSV approach is an important challenge for agribusiness companies. There are many areas where economic value can be augmented by new approach applications in agribusiness. Unfocused philanthropy, in the form of charitable donations and volunteering, should be replaced by the direct activity of companies aimed at solving social and environmental problems of agribusiness. Companies should make more effort towards shared value creation focused on reconceiving products and markets, redefining productivity in the value chain and building supportive agribusiness clusters. Some good practices presented in this study already are implemented. It contributes to identifying and gaining insight into the process of superseding CSR by the CSV approach in agribusiness, in Poland. This paper brings the discussion about social responsibility in agribusiness to a new level.
[Introduction] (The SOH(State of Health) evaluation of lithium-ion batteries is difficult to meet the on-board environment requirements of electric vehicles because of the dispersion of evaluation results was caused by the inconsistent characteristics of batteries. [Method] To solve the problem, the corresponding changes of open circuit voltage curve, pulse voltage response and incremental capacity curve of typical energy storage component NCM battery during life cycle test were analyzed. 6 characteristic variables which were closely related to the battery capacity loss were selected, and a comprehensive SOH evaluation method based on fuzzy logic was proposed. In this method, membership function was used to establish the relationship between SOH evaluation sets and variable indicators, and analytic hierarchy process based on correlation coefficient was used to determine the weights of variable indicators that have an impact on the evaluation results. Finally, the validity of the proposed method was verified by four NCM-21700 batteries that completed the life cycle test. [Result] The results show that the method can effectively reduce the dispersion of SOH evaluation, and the average error is not more than 3% as well as the maximum error is no more than 5%. [Conclusion] This work provides some guidance for further study on state of health evaluation of lithium-ion batteries.
The world is witnessing increasing frequency of extreme events. The power system is the backbone critical infrastructure of our economy and is under treat of such events. The resilient power system is intended to cope with low probability, high risk extreme events including extreme natural disasters and man-made attacks. Realizing resilience in the power system has been an unprecedented mission. Equipped with today’s smart grid technologies, power system can be rendered more resilient by the strategies taken before, during and after a disruptive event erupts. Based on a thorough review of existing works, we present the most-investigated problems and solving measures according to their application stage. In the preparation stage, innovative planning frameworks considering disaster scenarios are discussed; after the event, the system can alter the topology and integrate resource allocation to alleviate load shedding. The characteristics of different disasters are investigated to facilitate enhancing resilience. The review provides a summary of resilience strategies in the power system and can shed light to future research and application. Keywords: Power system, Resilience, Critical infrastructure, Extreme event, Natural disaster
Energy conservation, Energy industries. Energy policy. Fuel trade
The development of Mycorrhizal Arbuscular Fungi (MAF) in general is influenced by the conditions of the rhizosphere and fungi spores. Rhizosphere conditions are conditions around the roots such as temperature, pH, and root exudates. While the condition is a fungal spore dormancy and maturity spores. The aim of this study was to determine the amount of FMA on some plantation crops rhizosphere, to determine the type of crop rhizosphere FMA on some plantations, as well as to determine the dominance of FMA on some plantation crops rhizosphere. The experiment was conducted at the Laboratory Analysis State Polytechnic of Lampung. Month trial period from December 2014 to July 2015. The method used in this study is a description of the method by observation. Based on research results and observations of mycorrhizal spores in the rhizosphere of plants cocoa, rubber, coffee, and palm oil was found that on average the highest number of spores found in oil palm plantations (2.4 spores), while the lowest number of spores present in the rubber plantations (1 spore ). Type spores on all plantation crops rhizosphere dominated by species Glomus with different types (10 types). Glomus Type 2 dominates on all plantation crops rhizosphere.
Keywords: estate crop, mycorrhizae, rhizosphere
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