|M.Sc Student||Bengio Shai|
|Subject||Remote Sensing of Diesel Vehicle Emissions|
|Department||Department of Mechanical Engineering||Supervisors||Professor Emeritus Yoram Zvirin (Deceased)|
|Dr. Leonid Tartakovsky|
|Full Thesis text|
The problem of air pollution by motor vehicles is becoming severe in the world.
There are several methods for measuring concentrations of pollutants emitted by vehicles, including remote sensing (RS) methods. The existing commercial RS systems have several inherent problems: they are expensive, the measurements sometimes are unreliable, the system set-up is complicated, and they usually require complex calibration schemes.
The present research work was aimed at developing the theory and design of dual remote sensing system for diesel and sparks ignition vehicles, focusing on the former. The design integrates a LIDAR based module for PM detection and concentration, with spectroscopy technique for gaseous emissions measurements, suitable for on-road remote sensing applications.
The novel approach is based on a concept of single ended LIDAR which depends on the scattering or back-scattering as a primary means for measuring the concentrations of species of interest. The remote sensing system developed in the research work is a dual one for measuring gas and particulate matter concentrations. The PM part has a LIDAR as the main component.
There were several research objectives in the current research, while the main goal was to design a remote sensing emissions measurement system with the following characteristics, High reliability, Low cost, dual system and Automatic (unmanned) operation.
Validation of the design and concept of the proposed system were done by numerical and analytical methods. The main objective was to model the scattering of light in the exhaust plume and select an optimal spectral range for the system operation regime, considering the Signal to Noise Ratio (SNR) and detector restrictions. Another objective was to validate the optical layout and to model modules and the entire system performance by utilizing the scattering data to perform full ray tracing and optical simulation of the system with illumination CAD software.
This has been concluded after evaluating the signals that would be measured by the detectors relative to the noise levels that should occur in the sensor during the pollution measurements, and from the detector measurement we have evaluated the concentration of the vehicle’s emission.
In this research the radiation scattering efficiencies of the particles were calculated according to Mie theory. Spectral radiation properties of particulate matter were explored. The LIDAR theory was employed for validation of the design of the system for PM detection and concentration measurement. The simulation results convincingly validated the design concept and confirmed the practicability of the system.