Forecasting electric vehicles sales with univariate and multivariate time series models: The case of China.

The market demand for electric vehicles (EVs) has increased in recent years. Suitable models are necessary to understand and forecast EV sales. This study presents a singular spectrum analysis (SSA) as a univariate time-series model and vector autoregressive model (VAR) as a multivariate model. Empirical results suggest that SSA satisfactorily indicates the evolving trend and provides reasonable results. The VAR model, which comprised exogenous parameters related to the market on a monthly basis, can significantly improve the prediction accuracy. The EV sales in China, which are categorized into battery and plug-in EVs, are predicted in both short term (up to December 2017) and long term (up to 2020), as statistical proofs of the growth of the Chinese EV industry.

Robust optimization on sustainable biodiesel supply chain produced from waste cooking oil under price uncertainty.

Waste cooking oil (WCO)-for-biodiesel conversion is regarded as the "waste-to-wealthy" industry. This paper addresses the design of a WCO-for-biodiesel supply chain at both strategic and tactical levels. The supply chain of this problem is studied, which is based on a typical mode of the waste collection (from restaurants' kitchen) and conversion in the cities. The supply chain comprises three stakeholders: WCO supplier, integrated bio-refinery and demand zone. Three key problems should be addressed for the optimal design of the supply chain: (1) the number, sizes and locations of bio-refinery; (2) the sites and amount of WCO collected; (3) the transportation plans of WCO and biodiesel. A robust mixed integer linear model with muti-objective (economic, environmental and social objectives) is proposed for these problems. Finally, a large-scale practical case study is adopted based on Suzhou, a city in the east of China, to verify the proposed models.

Silica-sol-based spin-coating barrier layer against phosphorous diffusion for crystalline silicon solar cells.

The phosphorus barrier layers at the doping procedure of silicon wafers were fabricated using a spin-coating method with a mixture of silica-sol and tetramethylammonium hydroxide, which can be formed at the rear surface prior to the front phosphorus spin-on-demand (SOD) diffusion and directly annealed simultaneously with the front phosphorus layer. The optimization of coating thickness was obtained by changing the applied spin-coating speed; from 2,000 to 8,000 rpm. The CZ-Si p-type silicon solar cells were fabricated with/without using the rear silica-sol layer after taking the sheet resistance measurements, SIMS analysis, and SEM measurements of the silica-sol material evaluations into consideration. For the fabrication of solar cells, a spin-coating phosphorus source was used to form the n(+) emitter and was then diffused at 930°C for 35 min. The out-gas diffusion of phosphorus could be completely prevented by spin-coated silica-sol film placed on the rear side of the wafers coated prior to the diffusion process. A roughly 2% improvement in the conversion efficiency was observed when silica-sol was utilized during the phosphorus diffusion step. These results can suggest that the silica-sol material can be an attractive candidate for low-cost and easily applicable spin-coating barrier for any masking purpose involving phosphorus diffusion.