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Lithium-ion cells are preferred in the electrical powertrain due to high-power density, compactness, and modularity. In real driving conditions, the cells undergo discharge rates as high as 4 C resulting in high heat generation affecting the performance. To obtain the maximum performance the pack construction and thermal management of cells are crucial parameters. In our work, air-cooled technique with diverse air inlet and staggered scheme with a two-channel partition approach for thermal management of the cylindrical lithium-ion cells are studied in computational fluid dynamics. The simulation model is validated with experimental results. The obtained results demonstrate that the cells in the dual-directional air inlet arrangement had low maximum temperature difference among and within the cells and required least fan work. This arrangement required least fan work to generate optimal air inlet velocity of 2 m/s for 1, 2, and 3 C and 4 m/s for 4 C discharge rates. There is a reduction of 50% and 33% fan work for 3 and 4 C discharge rates, which are the majority operating points. Also, it shows that the temperature uniformity within the cells has improved. The results of this study can used to optimize parameters for designing an enhanced thermal management system.  相似文献   
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Energy production systems such as proton-exchange membrane fuel cell (PEMFC) has a promising future in the cleaner energy market due to zero emissions. Rubber pad forming (RPF) process of metallic bipolar plates of PEMFCs is gaining attention among the researchers. Studies based on design of experiments have been conducted to find the crucial parameters of the forming process. These methods are based on the assumptions of the model structure, correlated residuals, etc., which can cause uncertainty in estimation ability of the model on unseen data. Therefore, the present study focuses on the design of robust models of these parameters for PEMFCs using an optimization approach of genetic programming (GP). The inputs from the experiments considered in GP are radius, the friction coefficient, the filling factor and the minimum thickness. Experiments on PEMFCs validates the performance of the GP models. Further, the relationships between the two inputs and the three outputs for PEMFCs are generated as well as the contributions of each input to each of the output. Optimization of the models generated by GP can further determine the forming quality of metallic bipolar plates of PEMFCs by an appropriate setting of the two inputs.  相似文献   
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New methods for synthesis of active materials have been developed to improve capacity and cycle life performance of lithium‐ion batteries. Past studies have focused on routes of development of materials and new processes, which might not be economical for large‐scale production. In this regard, this study examines a widely employed carbothermal reduction technology for the synthesis of lithium‐iron phosphate (LiFePO4/C) and investigates effects of process conditions during this synthesis on final battery performance. An experimental combined genetic programming approach is used to model the effects of crucial process conditions (sintering time, the carbon content, and the sintering temperature) on the discharge capacity of the assembled battery. Experiments are conducted to collect the discharge capacity data based on varying LiFePO4/C synthesis conditions, and genetic programming is employed to develop a suitable functional relationship between them. The results show that the battery discharge capacity is controlled significantly by adjusting sintering temperature and carbon content, while the effect of sintering time is found to be insignificant. Further, the interaction effect of the sintering time and carbon content is much more obvious than that of the sintering time and the sintering temperature. The findings from the study pave the way for the optimum design of the synthesis process of LiFePO4/C for a higher battery performance.  相似文献   
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The mechanisms in proton‐exchange membrane fuel cells (PEMFCs) cannot be explicitly represented by a mathematical function because the PEMFC system is multi‐dimensional and complex and represents uncertainty in operation variables, which cannot be modeled by experiments or by trial‐and‐error approach. Therefore, this work proposes to study the coupled and interactive influence of stack current (SC), stack temperature (ST), oxygen excess ratio (OER), hydrogen excess ratio (HER), and inlet air humidity (IAH) for optimizing the power output of PEMFC. The data obtained from the experiments have been inserted into architecture of automated neural‐network search, which automates the selection of error function, activation function, uncertainties in inputs and number of hidden neurons in formulation of a robust and accurate model for power density as a function of five operational variables. Among the operational variables, the correlation coefficient between the SC and the output power is the highest, followed by OER, and the ST. However, for HER and IAH, the power output follows negative nonlinear relation. The optimization converged at 130th iteration results in maximum power output of 3410 W for an optimum value of SC (51A), ST (59°C), OER (3:2), HER (1:10), and IAH (0.8).  相似文献   
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A methodology is proposed to reduce the cost and capital intensity of small-scale chemical processes by creating new opportunities for economies of numbers through standardizing the equipment designs across multiple processes. We depart from asynchronous design of single-processes and adopt a common-functionality based simultaneous design of multiple processes that use similar unit operations. A generalized cost function is used to appropriately balance the trade-offs between economies of scale and economies of numbers. An optimization-based framework for design standardization is developed and illustrated using two case studies. The first involves the simultaneous synthesis of methanol and ammonia processes, and the second addresses the optimal synthesis of multi-column natural gas liquid (NGL) fractionation processes for different natural gas sources. We observe that considerable reduction in capital intensity of small-scale processes is possible through equipment standardization.  相似文献   
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A model cancer cell line was used to initiate polymerisation of pyrrole to form the conducting material polypyrrole. The polymerisation was shown to occur through the action of cytosolic exudates rather than that of the membrane redox sites that normally control the oxidation state of iron as ferricyanide or ferrocyanide. The data demonstrate for the first time that mammalian cells can be used to initiate synthesis of conducting polymers and suggest a possible route to detection of cell damage and/or transcellular processes through in situ and amplifiable signal generation.  相似文献   
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In this paper, a method composed of state of health (SOH) testing experiments and artificial intelligence simulation is proposed to carry out the study on the change of battery characteristic during its operation and generate mathematical models for the prediction of aging behaviour of battery. An experiment comprising of multidisciplinary parameters-based SOH detection is conducted to study the battery aging characteristics from several aspects (ie, electrochemistry, electric, thermal behaviour and mechanics). In total, 200 sets of data (corresponding 200 charging/discharging cycles) are collected from the experiment. The data obtained from the first 150 cycles are employed in generation of the models. The result of sensitivity analysis based on the obtained genetic programming models shows that it is better to apply voltage value at the end of charging step, charging time and cycle number to predict the operational performance of the battery. The average predicted accuracy of model (without stress) is 94.52%, whereas the average predicted accuracy of model (with stress effect) is 99.42%. The proposed models could be useful for defining the optimised charging strategy, fault diagnosis and spent batteries disposal strategies.  相似文献   
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The present research proposes a combined framework that evaluates remaining capacity, material behavior, ions concentration of remaining metals, and current rate of chemical reactions of spent Li‐ion batteries accurately. Voltage, temperature, internal resistance, and capacity were studied during charging and discharging cycles. Genetic programming was applied on the obtained data to develop a model to predict remaining capacity. The results of experimental work and those estimated from model were found to be correlated, confirming the validation of model. Materials structure and electrochemical behavior of electrodes during cycles were studied by cyclic voltammetry, scanning electron microscopy, and energy dispersion spectrum.  相似文献   
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