Abstract: This paper proposes a novel battery cell balancing topology with reduced component count and simplified control. The balancing algorithm is based on the state of charge (SOC) of each individual cell instead of cell voltage. The principle of the proposed topology is analyzed and verified through simulation and experiments. Then an experimental battery test workbench is established to validate the proposed balancing algorithm. The experimental results show that the proposed balancing topology and associated algorithm can perform well in real applications.
Abstract: This paper presents a model-based cell-health-conscious thermal energy management method. An Arrhenius equation-based mathematical model is firstly identified to quantify the effect of temperature on the cell lifetime of a Nickel Metal Hydride (NiMH) battery pack. The cell aging datasets collected under multiple ambient temperatures are applied to extract the Arrhenius equation parameters. The model is then used as an assessment criterion and guidance for the thermal management design of battery packs. The feasibility and applicability of a pack structure with its cooling system, is then evaluated, and its design problems are studied by a computational fluid dynamics (CFD) analysis. The performance and eligibility of the design method is validated by both CFD simulations and experiments.
Abstract: In the first part of this work, combined heat and power (CHP) criteria pertaining to energy, exergy, environmental (pollutant emission) and economic aspects, have been investigated and compared. Although the constraints in legislation usually refer to energy efficiency, primary energy savings and greenhouse gas savings, other criteria should also be taken into account in order to obtain a better evaluation of a cogeneration plant. Here particular attention has been paid to saving indexes for both an individual CHP-unit and for a CHP-system, that is the complete system with all the cogeneration units and the auxiliary plants necessary to cover the users’ demand. Five indexes, named potential indexes, have been introduced to evaluate the cogeneration potential: one for energy saving, one for exergy, two for environmental aspects (global and local scale) and one for economic aspects. Finally, some indexes analysed in the paper have been applied to a case study concerning a district heating cogeneration system, and the different behaviour of the energy-exergy, environmental and economic aspects has been discussed.
Abstract: The promotion of hybrid and electric vehicles (EVs) has been proposed as one promising solution for reducing transport energy consumption and mitigating vehicular emissions in China. In this study, the energy and environmental impacts of hybrid and EVs during 2010–2020 were evaluated through an energy conversion analysis and a life cycle assessment (LCA), and the per-kilometer energy consumptions of gasoline, coal, natural gas (NG), oil, biomass, garbage and electricity for EVs and HEVs were estimated. Results show that the EVs and HEVs can reduce the energy consumption of vehicles by national average ratios of 17%–19% and 30%–33%, respectively. The study also calculated the detailed emission factors of SO2, NOX, VOC, CO, NH3, PM10, PM2.5, OC, EC, CO2, N2O, CH4, Pb and Hg. It is indicated that the HEVs can bring significant reductions of NOX, VOC and CO emissions and lesser decreases of SO2 and CO2 for a single vehicle. The EVs could decrease many of the VOC, NH3, CO and CO2 emissions, but increase the SO2, NOX and particles by 10.8–13.0, 2.7–2.9 and 3.6–11.5 times, respectively. In addition, the electricity sources had significant influence on energy consumption (EC) and emissions. A high proportion of coal-fired energy resulted in large ECs and emission factors. The total energy consumption and pollutants emission changes in 2015 and 2020 were also calculated. Based on the energy use and emission analysis of HEVs and EVs, it is suggested that EVs should be promoted in the regions with higher proportions of hydropower, natural gas-fired power and clean energy power, while HEVs can be widely adopted in the regions with high coal-fired power ratios. This is to achieve a higher energy consumption reduction and pollutant emission mitigation. Moreover, the results can also provide scientific support for the total amount control of regional air pollutants in China.
Abstract: This paper compares the greenhouse gas (GHG) emissions of natural gas (NG)- based fuels to the GHG emissions of electric vehicles (EVs) powered with NG-to-electricity in China. A life-cycle model is used to account for full fuel cycle and use-phase emissions, as well as vehicle cycle and battery manufacturing. The reduction of life-cycle GHG emissions of EVs charged by electricity generated from NG, without utilizing carbon dioxide capture and storage (CCS) technology can be 36%–47% when compared to gasoline vehicles. The large range change in emissions reduction potential is driven by the different generation technologies that could in the future be used to generate electricity in China. When CCS is employed in power plants, the GHG emission reductions increase to about 71%–73% compared to gasoline vehicles. It is found that compressed NG (CNG) and liquefied NG (LNG) fuels can save about 10% of carbon as compared to gasoline vehicles. However, gas-to-liquid (GTL) fuel made through the Fischer-Tropsch method will likely lead to a life-cycle GHG emissions increase, potentially 3%–15% higher than gasoline, but roughly equal to petroleum-based diesel. When CCS is utilized, the GTL fueled vehicles emit roughly equal GHG emissions to petroleum-based diesel fuel high-efficient hybrid electric vehicle from the life-cycle perspective.
Abstract: This paper proposes a new model for short-term forecasting of electric energy production in a photovoltaic (PV) plant. The model is called HIstorical SImilar MIning (HISIMI) model; its final structure is optimized by using a genetic algorithm, based on data mining techniques applied to historical cases composed by past forecasted values of weather variables, obtained from numerical tools for weather prediction, and by past production of electric power in a PV plant. The HISIMI model is able to supply spot values of power forecasts, and also the uncertainty, or probabilities, associated with those spot values, providing new useful information to users with respect to traditional forecasting models for PV plants. Such probabilities enable analysis and evaluation of risk associated with those spot forecasts, for example, in offers of energy sale for electricity markets. The results of spot forecasting of an illustrative example obtained with the HISIMI model for a real-life grid-connected PV plant, which shows high intra-hour variability of its actual power output, with forecasting horizons covering the following day, have improved those obtained with other two power spot forecasting models, which are a persistence model and an artificial neural network model.
