Search Results

Solenoids are type of inductive actuators extensively used in mobility industries as flow control valves. Now a day, the conventional mechanical actuators are replaced by solenoids, because the solenoids have high precision control and faster response within a controlled magnetic field. Solenoids are classified into two types based on the mode of operation. Solenoid is operated either in ON/OFF mode for switching applications or in Pulse Width Modulation (PWM) for high frequency applications. A solenoid consists of two critical parts, one is the reciprocating plunger and another is the static valve case. During higher number of repeated operations, the solenoid plunger hits the valve case and induces wear on the seating surface. The solenoids are also exposed to the corrosive environment in some applications.

The automotive industry in world is facing the problem of reduction of emissions coming out of the engine. Also, the stringent emission norms imposed by the regulating body for transition from BS IV to BS VI urges the auto makers to concentrate on new technologies to reduce the emissions. One of the major emissions coming out of the diesel engine is oxides of nitrogen (NOx) which is detrimental to human health. This NOx emission is formed when the combustion temperature of engine exceeds the threshold limit. There are several methods available to reduce these NOx emissions formed in-cylinder. Exhaust Gas Recirculation (EGR) is one such system, which reduces the NOx emission formed inside the engine by supplying a portion of the exhaust gases. By re-circulating exhaust gases, the air admitted to the engine is diluted. Further, due to the high latent heat of vaporization of water, water vapor tends to absorb more amount of heat that is generated during combustion.

This paper presents the details of the study to optimize and arrive at a design base for a vacuum pump in an automotive engine using resilient back propagation algorithm for Artificial Neural Networking (ANN). The reason for using neural networks is to capture the accuracy of experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. Vacuum Pump is an engine driven part. Design and optimization of a vacuum pump in an automotive engine is crucial for development. The NN predicted values had a good correlation with the actual values of tested proto sample. The design optimization by means of this study has served the purpose of generating the data base for future development of different capacity vacuum pumps.

Increasing the efficiency of the Engine parts and reduction in development time with good accuracy are the challenges in the Automotive Industry. Lubricating oil pump has been selected for this study. Existing literatures explain the methodology to generate the rotor profile from the given geometrical parameters of the rotor like eccentricity, tooth radius etc. Invariably the specifications to design the pump are provided in terms of pump performance at various operating conditions. The analytical model developed in this study uses the performance and boundary specifications to generate the rotor profile and to estimate the flow rate at various operating conditions of the pump. This methodology includes the generation of trochoidal profile for inner rotor and modified conjugate profile for the outer rotor and the volume calculation of number of chambers (N) which are created between the rotors during meshing.