TY - GEN
T1 - Intelligent eco-driving suggestion system based on vehicle loading model
AU - Chou, Wei Yao
AU - Lin, Yi Chun
AU - Lin, Yu Hui
AU - Chen, Syuan Yi
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Eco-Driving Assistance System
KW - Fuel economy
KW - On-Board Diagnostic
KW - Smart Vehicle Information Gateway
UR - http://www.scopus.com/inward/record.url?scp=84874494112&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874494112&partnerID=8YFLogxK
U2 - 10.1109/ITST.2012.6425241
DO - 10.1109/ITST.2012.6425241
M3 - Conference contribution
AN - SCOPUS:84874494112
SN - 9781467330701
T3 - 2012 12th International Conference on ITS Telecommunications, ITST 2012
SP - 558
EP - 562
BT - 2012 12th International Conference on ITS Telecommunications, ITST 2012
T2 - 2012 12th International Conference on ITS Telecommunications, ITST 2012
Y2 - 5 November 2012 through 8 November 2012
ER -