Integrated artificial intelligence and life cycle assessment to predict environmental and economic impacts for natural gas hybrid electric vehicle with multi-dimension

Abstract

Abstract The automotive industry plays very significant role in Chinese industry. but higher energy consumption and higher pollution accompanying with the vehicle’s industry chain as well. natural gas for vehicles has the characteristics of cleanness, economy and reliability. Therefore, the hybrid vehicle with both advantages of natural gas and electricity has great potential. However, it is unclear that the promotion of natural gas / electric hybrid vehicles (NGEHV) could really achieve energy saving and emission reduction. In this paper, consider all stages vehicle production, transportation, use, maintenance and scrap recovery, the possession is decomposed into three aspects: resource attributes, energy attributes and environmental attributes. An composition analysis method of NGEHV is constructed. A life cycle assessment(LCA), in the view of Cradle-to-Grave, of environmental impact for natural gas / electric hybrid vehicles is established. Based on BP neural network, prediction information of traditional vehicles and NGEHV on various environmental factors and costs are obtained. It could provide scientific basis for the sustainable advancement and decision-making for government.