Narongkorn Uthathip^1,*, Pornrapeepat Bhasaputra¹, Woraratana Pattaraprakorn²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 69-86, 2022, DOI:10.32604/csse.2022.020120

Abstract Generally, road transport is a major energy-consuming sector. Fuel consumption of each vehicle is an important factor that affects the overall energy consumption, driving behavior and vehicle characteristic are the main factors affecting the change of vehicle fuel consumption. It is difficult to analyze the influence of fuel consumption with multiple and complex factors. The Adaptive Neuro-Fuzzy Inference System (ANFIS) approach was employed to develop a vehicle fuel consumption model based on multivariate input. The ANFIS network was constructed by various experiments based on the ANFIS Parameter setting. The performance of the ANFIS network was validated using Root Mean Square… More >

Xiaobin Shu, Miaomiao Ren^*

FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.5, pp. 1019-1029, 2020, DOI:10.32604/fdmp.2020.09564

Abstract In order to address typical problems due to the huge demand of oil for consumption in traditional internal combustion engines, a new more efficient combustion mode is proposed and studied in the framework of Computational Fluid Dynamics (CFD). Moreover, a Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied to optimize the related parameters, namely, the engine methanol ratio, the fuel injection time, the initial temperature, the Exhaust Gas Re-Circulation (EGR) rate, and the initial pressure. The so-called Conventional Diesel Combustion (CDC), Homogeneous Charge Compression Ignition (HCCI) and the Reactivity Controlled Compression Ignition (RCCI) combustion modes are compared. The results show that… More >