Intelligent eco-driving suggestion system based on vehicle loading model

Abstract

Eco-driving skill has been getting more and more attentions because of global warning and increasing oil price. So far, existing eco-driving assistance systems mainly offered raw instantaneous fuel economy to driver. However, inexperience driver still had the difficulty to turn raw fuel economy information into proper eco-driving behavior. For this situation, an intelligent eco-driving suggestion system based on vehicle loading model was developed. The instantaneous fuel economy was computed according to the information from vehicle on board diagnostic system. In addition, fuzzy inference system was applied to estimate eco-level and fuzzy rules were utilized to establish a vehicle loading model. The appropriate eco-driving suggestion was analyzed by built-in artificial intelligence and can be displayed on any Android portable device. Finally, the developed eco-driving suggestion system was ported on Smart Vehicle Information Gateway, installed on real vehicle and tested on real track. The experimental results proved that 7% fuel economy can be improved.