Emissions from represent a major component of airborne pollution. Transportation emission models are part of the modeling process of transportation planning. It introduces an important tool for the environmental evaluation of different transportation scenarios. Worldwide, there are several emission models. These models are categories to static and dynamic models. It depends on the amount of available data for the emission modeling. Monitoring emissions in a study area is also an important tool of validating such emission models. In this paper, an analysis and comparison between transport emission models are used in estimating emissions from road traffic systems in urban areas has been introduced. The paper discusses the limitations and potentials of each type of transport emission models. The difficulties against applying these models in developing countries are also discussed. The study also determines the required steps towards realistic modeling of emission from transportation systems in developing countries. Moreover, different methods used for road traffic emission monitoring have been investigated.
The greater the use of energy in the transportation sectors, the higher the emission of carbon monoxide (CO), and hence inevitable harm to environment and human health. In this concern, measuring and predicting of CO emission from transportation sector-especially large cities-is important as it constitute 90 % of all CO emission. Many urban cities in developing world have not properly experienced such measurements or predictions. In this paper, for the first time, field measurements of traffic characteristics data and corresponding CO concentration have been performed for developing a model for predicting CO emissions from transportation sector for New Borg El Arab (NBC), Egypt. The performance of Swiss-German Handbook Emission Factors for Road Transport (HBEFA v3.1) model has been assessed for predicting the CO concentration at roadside in the study area. Results indicated that HBEFA v3.1 underestimate emission figures. The developed CO dynamic emission model involves the traffic flow characteristics with roadside CO concentrations. Acceptable representation of measured CO concentration has been shown by the developed dynamic CO emission model which introduces R (2) = 0.77, mean biases and frictional biases of -0.27 mg m(-3) and 0.09, respectively. A comparison between predicted CO concentrations using HBEFA v3.1 and the promoted dynamic model indicate that HBEFA v3.1 estimates CO emission concentrations in the study area with a mean error and frictional biases 159.26 and 233.33 %, respectively, higher than those of the developed model.
Steer-by-wire (SBW) systems in a passenger car can improve vehicle steering capability and design flexibility by replacing the mechanical linkage between the steering wheel and front wheels by a control circuit. The steering controller, however, should provide good performance in response to driver's input signal. This includes fast response, absence of overshoot or oscillatory behavior, and good accuracy with minimal steady-state error. In this paper, an optimal control strategy based on observed system states is proposed and implemented on an electrohydraulic SBW system of a passenger car. First, a linear mathematical model is developed using gray-box system identification techniques. A standard input signal, pseudorandom binary sequence (PRBS), is designed to stimulate the system in the concerned bandwidth. Then, a linear-quadratic regulator (LQR) together with a full-state system observer is designed. Based on simulation, the LQR parameters and the observer poles are chosen to satisfy the aforementioned performance criteria for good steering. Finally, the control strategy is applied in a real-time environment to test the tracking capability, where the system is given high-rate reference signals (relative to the human rate of steering). The results show that the steering system tracks the reference signal with high accuracy even in the existence of high external force disturbances.
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