Optimizing fuel consumption and pollutant emissions of gasoline-HEV with catalytic converter

Because of more and more stringent vehicle emission standards, Hybrid Electric Vehicles (HEV) are developed. Gasoline-HEV are equipped with 3-Way Catalytic Converter (3WCC). So the energy management systems of such vehicles, which must reduce not only fuel consumption, but also vehicle pollutant emissions, have to consider the 3WCC heating. A pollutant constrained energy management strategy is presented. A 3WCC multi-0D model is built from physical equations, with a good complexity-performances compromise. An off-line optimal strategy allows the joint minimization of pollution and fuel consumption with only one parameter to tune, while considering all the standardized pollutant emissions. This strategy reduces significantly the vehicle emissions for a minor fuel consumption increase and leads to define 3WCC smart heating. Thus an on-line smart heating strategy is implemented in a HyHIL (Hybrid Hardware In the Loop) test bench, reducing the pollutant emissions of the classical charge sustaining strategy by 30% for CO and 10% for NO_X.     

An error correction framework for sequences resulting from known state-transition models in Non-Intrusive Load Monitoring

Non-Intrusive Load Monitoring (NILM), the set of techniques used for disaggregating total electricity consumption in a building into its constituent electrical loads, has recently received renewed interest in the research community, partly due to the roll-out of smart metering technology worldwide. Event-based NILM approaches (i.e., those that are based on first segmenting the power time-series and associating each segment with the operation of electrical appliances) are a commonly implemented solution but are prone to the propagation of errors through the data processing pipeline. Thus, during energy estimation (the final step in the process), many corrections need to be made to account for errors incurred during segmentation, feature extraction and classification (the other steps typically present in event-based approaches). A robust framework for energy estimation should use the labels from classification to (1) model the different state transitions that can occur in an appliance; (2) account for any misclassifications by correcting event labels that violate the extracted model; and (3) accurately estimate the energy consumed by that appliance over a period of time. In this paper, we address the second problem by proposing an error-correcting algorithm which looks at sequences generated by Finite State Machines (FSMs) and corrects for errors in the sequence; errors are defined as state transitions that violate the said FSM. We evaluate our framework on simulated data and find that it improves energy estimation errors. We further test it on data from 43 appliances collected from 19 houses and find that the framework significantly improves errors in energy estimates when compared to the case with no correction in 19 appliances, leaves 17 appliances unchanged, and has a slightly negative impact on 6 appliances.     

Causal links between renewable energy,environmental degradation and economic growth in selected SAARC countries: Progress towards green economy

The objective of the study is to investigate the short-run and long-run causality relationship among energy (electricity production from renewable sources), carbon dioxide emissions, natural resource depletion, Gross Domestic Product (GDP) and poverty in selected SAARC countries, namely, Bangladesh, India, Nepal, Pakistan and Sri Lanka, over a period of 1975–2010. The results show that there is bidirectional Granger causality between carbon dioxide emissions & natural resource depletion in Nepal and between energy production & poverty in Pakistan. For the other three countries, the Granger causality runs from energy production to poverty in Bangladesh and India, and from poverty to energy production in Sri Lanka. The results of panel group Fully Modified OLS (FMOLS) indicates that GDP and poverty has a positive impact while carbon dioxide emission has a negative impact on energy production. Similarly, an increase in energy production leads to decrease in carbon emissions, where as, natural resource depletion increase carbon emissions in selected SAARC countries. Subsequently, an increase in energy production leads to increase in GDP which further increase carbon dioxide emission in SAARC region.     

Effect of K2O content on breakdown strength and energy-storage density in K2O-BaO-Nb2O5-SiO2 glass-ceramics

Phase evolution, dielectric properties, breakdown strength, and energy-storage performance were studied by varying K₂O content in K₂O-BaO-Nb₂O₅-SiO₂ glass-ceramics. It was found that dielectric loss with the increase of K₂O content increases owing to the un-crystallized K₂O into the glass network, while dielectric breakdown strength firstly increases and then decreases due to the competition between two physical mechanisms, i.e., interfacial polarization and bridging-oxygen bond broken by the non-bridging oxygen ions. With the increase of K₂O content, energy-storage density firstly increased up to 12.06±0.69 J/cm³ with a high breakdown strength of 1973 kV/cm, and then decreased. Also, the discharged efficiency is obtained as a high value of 92% from P-E hysteresis loops.     

Energy-efficient WiFi scanning for localization

WiFi radio signals are commonly used for the localization of mobile devices. However, frequent scanning of WiFi reduces user experiences because it consumes significant energy on mobile devices. In this paper, we propose an energy-efficient WiFi scan system for localization. The proposed system preserves the quality of service of each application and minimizes the energy consumption of WiFi scanning. The main idea is that the system adaptively controls the dwell time of beacon-listening in given locations. We predict the number of scanned access points (APs) according to locations and optimize the dwell time of beacon-listening to obtain the minimum number of scanned APs. The evaluation shows that the proposed system saves the energy consumption of WiFi scans by 33.6% and 45.7%, according to the number of scanned APs, while not decreasing the accuracy of localization in indoor and outdoor scenarios.     

Undergraduate studies in energy education – A comparative study of Greek and British courses

Undergraduate energy education in Greece is compared with relevant accredited courses of the United Kingdom, with the aim to transfer good practices applied in the latter for the development and improvement of the Greek courses. Despite the encouraging prospects for energy engineering courses, the situation in Greece seems declining, with only one course being offered in this period. The (unique) Greek course seems to share the same basis with the majority of the British accredited courses, but also a few peculiarities that could be amended for the improvement of the course.     

A portfolio of powertrains for the UK: An energy systems analysis

There has recently been a concerted effort to commence a transition to fuel cell vehicles (FCVs) in Europe. A coalition of companies released an influential McKinsey-coordinated report in 2010, which concluded that FCVs are ready for commercial deployment. Public–private H₂Mobility programmes have subsequently been established across Europe to develop business cases for the introduction of FCVs. In this paper, we examine the conclusions of these studies from an energy systems perspective, using the UK as a case study. Other UK energy system studies have identified only a minor role for FCVs, after 2030, but we reconcile these views by showing that the differences are primarily driven by different data assumptions rather than methodological differences. Some energy system models do not start a transition to FCVs until around 2040 as they do not account for the time normally taken for the diffusion of new powertrains. We show that applying dynamic growth constraints to the UK MARKAL energy system model more realistically represents insights from innovation theory. We conclude that the optimum deployment of FCVs, from an energy systems perspective, is broadly in line with the roadmap developed by UK H₂Mobility and that a transition needs to commence soon if FCVs are to become widespread by 2050.     

9号高炉热风炉1200℃风温攻关

新钢9号炉通过稳定高风温操作,为节焦降耗起到了良好的促进作用。     

Performance Study of a Closed-Type Heat Pump Tumble Dryer Using a Simulation Model and an Experimental Set-Up

In the interests of competitiveness, manufactures of tumble dryers are seeking to reduce both their electricity use and the drying time. This study examines how the cylinder volume of the compressor and the total heat transfer of the condenser influence the drying time and electricity use in a heat pump tumble dryer. A transient simulation model was developed and compared to an experimental set-up with good similarity. The simulations show that increasing the cylinder volume of the compressor by 50% decreases the drying time by 14% without using more electricity.