Framework of vehicle emission inspection and control through RFID and traffic lights

Vehicle emissions including carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) closely relate to air-ratio called lambda (λ) among all of the engine variables. Higher λ value indicates a significant amount of emissions harmful to our environment is produced and hence engine maintenance, particularly the catalytic converter, is necessary. Mandatory vehicle examination cannot be taken easily for each car, so it is difficult to enforce the vehicle owners on monitoring the health of their engines daily and taking immediate action to fix their vehicle emission problems. Traffic lights considered as “Things” through the concept of Internet of Things (IoT) can be applied because there are numerous traffic lights in an urban area. In addition, cars must stop on red lights so that reliable λ reading can be interrogated wirelessly through radio frequency identification (RFID). Simulation results show that the proposed application can effectively control and reduce vehicle emissions.

[1]  Derong Liu,et al.  Adaptive Critic Learning Techniques for Engine Torque and Air–Fuel Ratio Control , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Jean-Philippe Vasseur,et al.  Interconnecting Smart Objects with IP: The Next Internet , 2010 .

[3]  Marimuthu Palaniswami,et al.  Gaussian networks for fuel injection control , 2001 .

[4]  Marimuthu Palaniswami,et al.  Model Predictive Control of a Fuel Injection System with a Radial Basis Function Network Observer , 2002 .

[5]  Marimuthu Palaniswami,et al.  Model predictive control of a fuel injection system with a radial basis function network observer , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[6]  Laurence T. Yang,et al.  The Internet of Things: From RFID to the Next-Generation Pervasive Networked Systems , 2008 .

[7]  Hao Ying,et al.  Fuzzy Gain-Scheduling Proportional–Integral Control for Improving Engine Power and Speed Behavior in a Hybrid Electric Vehicle , 2009, IEEE Transactions on Vehicular Technology.

[8]  Chi-Man Vong,et al.  Case-Based Classification System with Clustering for Automotive Engine Spark Ignition Diagnosis , 2010, 2010 IEEE/ACIS 9th International Conference on Computer and Information Science.

[9]  Chi-Man Vong,et al.  Engine ignition signal diagnosis with Wavelet Packet Transform and Multi-class Least Squares Support Vector Machines , 2011, Expert Syst. Appl..

[10]  Chi-Man Vong,et al.  Case-based adaptation for automotive engine electronic control unit calibration , 2010, Expert Syst. Appl..