Dynamic Performance of a Bulkhead Flat Car

The dynamic performance of a flat car is studied herein. The performance indices include roll angles, lateral accelerations, center plate loads, side bearing loads, wheel loads and spring deflections. These variables are maximum when the car is running at its critical speed, corresponding to either the rock and roll, or the bounce mode. The Association of American Railroads' (AAR) Flexible Carbody Model was used. The input for vertical track irregularities used in the simulation was generated from published spectra for U.S. Federal Railroad Administration (FRA) Class 4 track. After studying the car's performance with various column loads and spring suspensions, it was found that the most commonly used column load of 4,000 lbs. (17.8 kN) should be used. The spring suspension used in the original car design should also be adopted, in order to avoid spring bottoming.     

Computer-Simulation of the Dynamical Curving Behaviour of a Railway-Bogie

This paper describes the modelling of a two axle railway-bogie with variable design configurations and its application in the investigation of the behaviour in transitional and circular curves. Several results indicate possibilities to improve the curving properties and recommend the usage of forced-steering bogies, which show better performance in narrow curves without unbearable sacrifices to high-speed-behaviour on straight track.     

Improvement of long-term lives of rubber gaskets of polyacrylate (ACM) by employing carboxyl cure sites

Rubber gaskets are used widely in many industries. An evaluation of the material properties and an accurate lifetime prediction of rubber are very important in the design process to ensure the durability and reliability of rubber components. The properties of rubber-like materials are sensitive to ambient conditions, such as temperature, environment and mechanical load. Moreover, the initial properties of rubber gaskets must be sustained under working conditions to maintain its sealing function. To perform tests within a reasonable time, the highly accelerated life test (HALT) is generally used to predict the long-term lifetime of rubber materials. Polyacrylate (ACM) with chlorine cure sites is generally used for engine head gaskets. An ACM with carboxyl cure sites was developed to improve the lifetime of the gaskets. A four-parameter method representing the recovery behavior of the gaskets was published recently, and two revised methods for obtaining the recovery were proposed. The mean squared errors (MSEs) of the regression methods and experimental data were compared. The life of a gasket for the target recovery (60%) of a compressed gasket was calculated somewhat differently depending on the selected regression model to predict a considerably different long-term life. The parameters in the regression models were obtained using the successive zooming genetic algorithm (SZGA), and the lives of ACM with a carboxyl cure site and ACM with a chlorine cure site were compared.     

Analysis of the shifting behavior of a novel clutchless geared smart transmission

Conventional geared transmissions use some kinds of clutches to control the power flow from an internal combustion engine to the driveline while shifting gears. However, the shifting performance is seriously affected by the clutch engagement and an unavoidable drop in the torque may occur when the clutch is disconnected. Moreover, wear of the clutch, the need for hydraulic equipment, and the load limit may together aggravate the limits of the clutch system. For this reason, as a novel transmission without a clutch, the clutchless geared smart transmission (henceforth CGST) is proposed by our research team. The CGST controls the power flow in a multiple-input gear-train by controlling the electric motor attached to the planetary gear system. However, no CGST has been realized in an actual vehicle thus far, and the performance has been predicted only theoretically. In this research, we analyzed the achievable performance based on a developed CGST dynamic model with a typical CGST structure. In addition, a CGST gear-shifting algorithm is proposed for use with the dynamic model. From the simulation results, the CGST does not show an abrupt drop in its torque or oscillation while shifting gears due to the absence of a discontinuous power flow. The developed dynamic model can serve as a performance reference for the CGST. Moreover, it can be used as a simulation tool for developing a gear-shifting control logic scheme.     

Preview suspension control for a full tracked vehicle

In this study, preview control algorithms for the active and semi-active suspension systems of a full tracked vehicle (FTV) are designed based on a 3-D.O.F model and evaluated. The main issue of this study is to make the ride comfort characteristics of a fast moving tracked vehicle better to keep an operator’s driving capability. Since road wheels almost trace the profiles of the road surface as long as the track doesn’t depart from the ground, the preview information can be obtained by measuring only the absolute position or velocity of the first road wheel. Simulation results show that the performance of the sky-hook suspension system almost follows that of full state feedback suspension system and the on-off semi-active system carries out remarkable performance with the combination of 12 on-off semi-active suspension units. The results simulated with 1^st and 2^nd weighting sets mean that the suspension system combined with the soft type of inner suspension and hard type of outer suspension can carry out better ride comfort characteristics than that with identical suspensions. The full tracked vehicle (FTV) system is uncontrollable and the system is split into controllable and uncontrollable subspace using singular value decomposition transformation. Frequency response curves to four types of inputs, such as heaving, pitching, rolling, and warping inputs, also demonstrate the merits of preview control in ride comfort. All the frequency characteristic responses confirm the continuous time results.     

Design and implementation of a UPnP-can gateway for automotive environments

In this paper, we propose a universal plug and play (UPnP) — controller area network (CAN) gateway system using UPnP middleware for interoperability between external smart devices and an in-vehicle network. The proposed gateway consists of a UPnP communication device, a CAN communication device, and a device translator layer. In-vehicle devices are not usually IP-based, so we implemented an in-vehicle device manager in the UPnP communication device which is in the gateway. We developed a vehicle simulator to produce real vehicular data for performance analysis. The CAN communication device transmits and receives real-time vehicle data between the real vehicular simulator and external devices through the UPnP. The device translator layer configures a message frame for enabling seamless data input and output between the CAN and UPnP protocols. After implementation, we generated an internal-external service request and tested the result. Finally, we confirmed the service request and operation between external devices and the internal vehicular device. Additionally, for a variety of external device numbers and communication environments, we demonstrated the gateway performance by measuring the round trip time (RTT) for overall service implementation.     

Artificial neural network approach to study the effect of injection pressure and timing on diesel engine performance fueled with biodiesel

This study intends to predict the influence of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with waste cooking palm oil based biodiesel using the artificial neural network (ANN) model. To acquire data for training and testing in the proposed ANN, experiments were carried out in a single cylinder, four stroke direct injection diesel engine at a constant speed of 1500 rpm and at full load (100%) condition. From the experimental results, it was observed that waste cooking palm oil methyl ester provided better engine performance and improved emission and combustion characteristics at injection pressure of 280 bar and timing of 25.5° bTDC. An ANN model was developed using the data acquired from the experiments. Training of ANN was performed based on back propagation learning algorithm. Multilayer perceptron (MLP) network was used for non-linear mapping of the input and output parameters. Among the various networks tested the network with two hidden layers and 11 neurons gave better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and was found to be very well correlated.     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

Real-time empirical NO<Subscript>x</Subscript> model based on In-cylinder pressure measurements for light-duty diesel engines

This paper proposes a real-time empirical model of NO_x emissions for diesel engines. The proposed model predicts the level of NO_x emissions using an empirical model developed based on the thermal NO formation mechanism, the extended Zeldovich mechanism. Since it is difficult to consider the exact physical NO formation phenomena in real-time applications, the proposed algorithm adapts the key factors of the NO formation mechanism from the extended Zeldovich mechanism: temperature of the burned gas, concentration of the gas species, and combustion duration where NO is generated. These factors are considered in a prediction model as four parameters: exhaust gas recirculation rate (EGR rate), crank angle location of 50 % of mass fraction burned (MFB50), exhaust lambda value, and combustion acceleration. The proposed prediction model is validated with various steady engine experiments that showed a high linear correlation with the NO_x emission measured by a NO_x sensor. Furthermore, it is also validated for transient experiments.