Will Limits of the Earth's Resources Control Human Numbers?

The current world population is 6 billion people. Even if we adopted a worldwide policy resulting in only 2.1 children born per couple, more than 60 years would pass before the world population stabilized at approximately 12 billion. The reason stabilization would take more than 60 years is the population momentum – the young age distribution – of the world population. Natural resources are already severely limited, and there is emerging evidence that natural forces already starting to control human population numbers through malnutrition and other severe diseases. At present, more than 3 billion people worldwide are malnourished; grain production per capita has been declining since 1983; irrigation per capita has declined 12% during the past decade; cropland per capita has declined 20% during the past decade; fish production per capita has declined 7% during the past decade; per capita fertilizer supplies essential for food production have declined 23% during the past decade; loss of food to pests has not decreased below 50% since 1990; and pollution of water, air, and land has increased, resulting in a rapid increase in the number of humans suffering from serious, pollution-related diseases. Clearly, human numbers cannot continue to increase.     

Integrated energy management strategy of powertrain and cooling system for PHEV

ABSTRACT

Energy management strategy (EMS) is crucial in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). Existing studies on EMS mostly manage powertrain and cooling system separately which cannot get the minimum total energy consumption. This paper aims to propose a novel EMS for a new type of dual-motor planetary-coupled PHEV, which considers cooling power demand and effect of temperature on fuel economy. Temperature-modified engine model, lithium-ion battery model, two motors, and cooling system models are established. Firstly, the separated EMS (S-EMS) is designed which manages powertrain and cooling system separately. Sequentially, after the analysis of thermal characteristics of the powertrain and cooling system, the thermal-based EMS (T-EMS) is then proposed to manage two systems coordinately. In T-EMS, cooling power demand and the charging/discharging energy of motors are calculated as equivalent fuel consumption and integrated into the object function. Besides, a fuzzy controller is also established to deicide the fuel-electricity equivalent factor with consideration of the effect of temperature and state of charge on powertrain efficiency. Finally, the hardware-in-loop experiment is carried out to validate the real-time effect of EMS under the New European Driving Cycle. The result shows that cooling power demand and temperature can significantly affect the fuel economy of the vehicle. T-EMS shows better performance in fuel economy than S-EMS. The equivalent fuel consumption of the cooling system of T-EMS decreases by 27% compared with that of S-EMS. The total equivalent fuel consumption over the entire trip of PHEV using T-EMS is reduced by 9.7%.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Analysis of the recycling system for aluminum cans,focusing on collection,transportation, and the intermediate processing methods

In this article, the systems for the collection and intermediate processing of used beverage cans (UBCs) are compared and analyzed, focusing on the time taken and the cost of processing, the energy consumption, and the emissions of CO₂, SO _x , and NO _x , during the process. We found that cases where the UBCs were crushed in the discharging process gave better results, and how the UBCs were collected was the most important factor. It was more desirable to treat UBCs in one place than in two places. When the transportation distance was longer, the pressed form of UBCs was more convenient. When the transportation distance was short, the original form, the crushed form, and the shredded form of UBCs were all suitable. That is, the contribution of the transportation process to the evaluation was large when the transport distance was long, and the contribution of the treatment process was large when the transport distance was short.     

组合优化的能源消费量预测模型

针对非等间距灰色系统预测中存在误差较大的问题，结合序列本身的特点，利用世界能源消费的历史数据，采用3种灰色预测模型与神经网络进行组合优化，建立了灰色神经网络的能源消费量组合预测模型。实证分析结果表明，提高了模型的拟合和预测精度，拓宽了应用范围。该模型可对能源的消费趋势进行预测，为科学分析能源结构提供依据。     

On the confluence of city living,energy saving behaviours and direct residential energy consumption

The purpose of this study is to shed light on the connection between income, dwelling type, tenure type and city living, in terms of both a household’s energy saving behaviours and direct residential energy consumption. This study employs data from the Household Energy Consumption Survey, Australia. Using a seemingly unrelated regression (SUR) system of equations the results reveal some key mechanisms which may allow householders to realise lower levels of energy consumption and hence lower carbon emissions. The results indicate that there are characteristics unique to living in a city that are linked to higher levels of direct residential energy consumption. On a number of measures (e.g. household income, tenure type and dwelling type), the results point to a lower likelihood of engaging in energy saving behaviours in cities. Also, depending on the number of energy saving behaviours, these actions have the potential to more than offset higher direct residential energy consumption of householders residing in separate houses. Coupled with these findings renters, a more vulnerable social group, are found to be significantly disadvantaged, suffering from a much lower adaptive capacity. Specifically, householders who rent their home are 77% less likely to have solar electricity. A result which may reflect differences in access to opportunity. Further, householders who rent are less likely to engage in energy saving actions. A finding which may reflect difference in ontological security and the greater psychological burden associated with undertaking energy saving behaviours (a barrier) borne by renters not shared with home owners.     

三烧溴化锂集中制冷空调系统改建设计

武钢三烧区域改建了二台大连三洋蒸汽型双效溴化锂吸收式制冷机。叙述了该改建项目的主机选型、参数选定、设计特点等。     

Decomposition Analysis of Sectoral Energy Use in Beijing （1981-2005） Using the LMDI Method

This paper aims to identify the main driving force for changes of total primary energy consumption in Beijing during the period of 1981-2005. Sectoral energy use was investigated when regional economic structure changed significantly. The changes of total primary energy consumption in Beijing are decomposed into production effects, structural effects and intensity effects using the additive version of the logarithmic mean Divisia index （LMDI） method. Aggregate decomposition analysis showed that the major contributor of total effect was made by the production effect followed by the intensity effect, and the structural effect was relatively insignificant. The total and production effects were all positive. In contrast, the structural effect and intensity effect were all negative. Sectoral decomposition investigation indicated that the most effective way to slow down the growth rate of total primary energy consumption （TPEC） was to reduce the production of the energy-intensive industrial sectors and improving industrial energy intensity. The results show that in this period, Beijing＇s economy has undergone a transformation from an industrial to a service economy. However, the structures of sectoral energy use have not been changed yet, and energy demand should be increasing until the energy-intensive industrial production to be reduced and energy intensity of the region reaches a peak. As sequence energy consumption data of sub-sectors are not available, only the fundamental three sectors are considered： agriculture, industry and service. However, further decomposition into secondary and tertiary sectors is definitely needed for detailed investigations.     

China's Present Situation of Coal Consumption and Future Coal Demand Forecast

This article analyzes China's coal consumption changes since 1991 and proportion change of coal consumption to total energy consumption. It is argued that power, iron and steel, construction material, and chemical industries are the four major coal consumption industries, which account for 85% of total coal consumption in 2005. Considering energy consumption composition characteristics of these four industries, major coal demand determinants, potentials of future energy efficiency improvement, and structural changes, etc., this article makes a forecast of 2010s and 2020s domestic coal demand in these four industries. In addition, considering such relevant factors as our country's future economic growth rate and energy saving target, it forecasts future energy demands, using per unit GDP energy consumption method and energy elasticity coefficient method as well. Then it uses other institution's results about future primary energy demand, excluding primary coal demand, for reference, and forecasts coal demands in 2010 and 2020 indirectly. After results comparison between these two methods, it is believed that coal demands in 2010 might be 2620-2850 million tons and in 2020 might be 3090-3490 million tons, in which, coal used in power generation is still the driven force of coal demand growth.     

智能电能表功耗测量系统软件设计

智能电能表功耗测量是一项重要的试验项目,介绍了电能表功耗测量仪和连接,着重分析了功耗测量系统软件的设计。该软件用于功耗测量数据采集,分析了其中的关键技术,给出了Lab VIEW设计框图。该软件实现了智能电能表功耗数据的自动化测量。