4 Search Results

We consider the design and operation of water networks simultaneously. Water network problems can be divided into two categories: the design problem and the operation problem. The design problem involves determining the appropriate pipe sizing and placements of pump stations, while the operation problem involves scheduling pump stations over multiple time periods to account for changes in supply and demand. Our focus is on networks that involve water co-produced with oil and gas. While solving the optimization formulation for such networks, we found that obtaining a primal (feasible) solution is more challenging than obtaining dual bounds using off-the-shelf mixed-integer nonlinearmore » programming solvers. Therefore, we propose two methods to obtain good primal solutions. One method involves a decomposition framework that utilizes a convex reformulation, while the other is based on time decomposition. To test our proposed methods, we conduct computational experiments on a network derived from the PARETO case study.« less

The technological advance of electrochemical energy storage and the electric powertrain has led to rapid growth in the deployment of electric vehicles. The high cost and the added weight of the batteries have limited the size (energy storage capacity) and, therefore, the driving range of these vehicles. However, consumers are steadily purchasing these vehicles because of the fast acceleration, quiet ride, and high energy efficiency. The higher pack-to-wheel efficiency and the lower energy cost per mile, as well as the lower expense for maintenance and repair, translate to operating savings over conventional vehicles. Here we compare battery electric vehicles withmore » internal combustion engine vehicles based on the total cost of ownership. It is seen that the higher initial cost of electric vehicles can be recovered in as little as 5 years. This is especially true for electric vehicles with shorter driving ranges. Specifically, a vehicle with an electric driving range under 200 miles may achieve cost parity with an equivalent internal combustion engine vehicle in 8 years or less.« less

In this work, the production of Lithium hexafluorophosphate (LiPF₆) for Lithium-ion battery application is studied. Spreadsheet-based process models are developed to simulate three different production processes. These process models are then used to estimate and analyze the factors affecting cost of manufacturing, energy demand, and environmental impact due to greenhouse gas (GHG) emissions. Moreover, the results indicate that in a facility with a capacity of making 10,000 metric tons per year of LiPF₆ the cost of production is around $20 per kg of LiPF₆, energy consumption is around 30 GWh per year, and the emission of greenhouse gases in CO_2-equivalentmore » gases is around 80 metric tons per day. The impact of change in process and economic parameters on the cost of production, energy demand, and emissions is studied. In addition, a few insights on reducing the cost of production are presented. Lastly, the impact of varying LiPF₆ costs on the overall cost of a Li-ion battery ($ kWh^-1) is presented.« less

In this paper, we study the design aspects and process dynamics of solvent removal from Lithium-ion battery electrode coatings. For this, we use a continuum level mathematical model to describe the physical phenomenon of cathode drying involving coupled simultaneous heat and mass transfer with phase change. Our results indicate that around 90% of solvent is removed in less than half of the overall drying time. We study the effect of varying temperature and air velocity on the drying process. We show that the overall drying energy can be reduced by at least 50% by using a multi-zone drying process. Also,more » the peak solvent flux can be reduced by at least 40%. We further present the effect of using an aqueous solvent instead of N-Methyl-2-pyrrolidone (NMP) in electrode drying. Our results indicate that Water dries nearly 4.5 times faster as compared to NMP and requires nearly 10 times less overall drying energy per kg of solvent.« less