Conceptual design of economic hybrid vehicle system using clutchless geared smart transmission

Most hybrid vehicles employ the continuously variable transmission (CVT or eCVT) currently as their choice of the transmissions. Recently, an automated geared transmission (AGT) or dual clutch transmission (DCT) is being tried for some hybrid vehicles for the better fuel economy than the CVT hybrid. However, this AGT or DCT is using automated clutches which require the hydraulic power in addition to the slippage in the clutch plate invoking some energy loss as well as wear. Also, they require a motor with significant power to match to the engine power. The clutchless geared smart transmission (CGST) has no clutch and the clutch function is performed by a planetary gear system controlled by a motor-generator. The hybrid vehicles proposed here using CGST may have some merits in durability, fuel efficiency, and cost since they do not have clutches. The motor used for the clutch function can be also working for power merge with the engine in propelling the vehicle. The proposed hybrid system can be either mild hybrid or full hybrid by adopting a different capacity of battery with much smaller motor-generator due to the planetary gear system compared to the other type hybrid vehicles. In this study, the prospects of newly proposed CGST hybrid system are examined in practical aspects compared with AGT hybrid or DCT hybrid systems.     

Operating speed pattern optimization of railway vehicles with differential evolution algorithm

The railway transportation system has much advantage in eco-friendliness, punctuality and safety compared to any other transportation system. Most of the railway system administrators have to control and operate under limited resources such as trains and facilities. It is necessary to control traveling time and energy consumption for efficient operation in the railway systems, because the board rate of passenger is inconstant with time variance. It is common that the shorter traveling time causes the greater energy consumption. In this study, a new optimization method considering operation time or energy consumption is proposed by using differential evolution algorithm and some cases are reviewed. The total energy change due to operation time variation are investigated by using the proposed optimization method for tangent and gradient track conditions. Both cases, the total energy decreases exponentially. However, because of gradient the total energy are saturated after a certain time for gradient track.     

Research on control strategy for differential steering system based on H mixed sensitivity

The differential steering system (DSS) of electric wheel vehicle gets rid of the restrictions of traditional steering system completely. As an ideal steering technology, it not only realizes the perfect combination of the road feel and the steering portability, but also realizes the harmony and unification between the steering maneuverability and safety. The structure and basic theory of the DSS of electric wheel vehicle are discussed in this paper. Based on these, the dynamic model of the steering system is built. Considering of the uncertainties and disturbances existing in the model, the H_∞ mixed sensitivity control theory is applied to achieve better tracking performance and road feel in the process of steering. Then, a H_∞ mixed sensitivity controller is designed to restrain the effect of the road disturbance and model uncertainties. The simulation results indicate that the DSS with the designed controller can effectively restrain the effect of noises and disturbances caused by random motivation from road, torque sensor measurement and model parameter uncertainty, and enable the driver to obtain satisfactory road feel.     

Modeling and control strategy development of a parallel hybrid electric bus

This paper presents the system modeling, control strategy design, and experiment validation of a parallel hybrid electric bus with an automatic manual transmission (AMT) and a dry clutch. The mathematical model representation and the system architecture of the powertrain are first described. Next, a complete control scheme including energy management strategy and coordinated control of the AMT and the clutch is presented. The controller and powertrain models are then integrated in a way that the power management and the hybrid driveline perform in real world. The analysis and validation through model simulation and comparison with experiment data are conducted. A good agreement between the model and experiment demonstrates the efficacy and credibility of the integrated model. The integrated model is employed in both simulation and bench-test assessments for the development of a hybrid control unit. The results indicate that the model-based design methodology is beneficial to systematically analyzing and understanding the dynamics of hybrid electric powertrain.     

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.     

Design and implementation of a new clamping force estimator in Electro-Mechanical Brake systems

In this paper, an improved clamping force estimator is proposed for Electro-Mechanical Brake (EMB) systems by using the motor rotor position information and the hysteresis characteristics of mechanical parts in the EMB. A cascaded type of a force/position control system with a force sensor or an estimator was designed and implemented to control the clamping force and to keep the clearance gap in EMB systems. The EMB Hardware-In-the-Loop-Simulation (HILS) results show that the proposed force estimator yields better estimation performance than the existing estimator and that the clamping force control system based on the estimator can be also used for the fault tolerant control of the system.     

Perceptions of foreign exchange rate risk in the shipping industry

This is an analysis of the impact of exchange rate risk on the performance of major shipping companies from two important maritime nations, Japan and Norway. For the shipping industry, such risk is exacerbated by freight rates fixed in US dollars which must then be converted into numerous other currencies. The appreciation of the Yen against the US dollar has been such that Japanese companies have been impelled to insulate themselves from exchange rate movements by natural hedging. For Norway, where fluctuations of the Krone against the US dollar have been less dramatic, exposure has been maintained, allowing an element of speculation. In both cases the market indicates that exchange rate risk is a significant factor in the determination of corporate performance.     

Evaluating the service requirements of dedicated container terminals: a revised IPA model with fuzzy AHP

The purpose of this article is to evaluate the service requirements of dedicated container terminals (DCTs). In this article, the service attributes (SAs) of DCTs were first discussed. A fuzzy analytic hierarchy process model was then constructed to measure the users’ perceived importance and dissatisfaction for each of the SAs. Based on these two measurements, a revised importance-performance analysis model was proposed to identify the SAs that should be improved. To validate the model, the dedicated container terminal of Evergreen Marine Corp. (EMC DCT) at Kaohsiung Port and its users were empirically investigated. With respect to the empirical results, managerial implications of the findings in improving service quality for the EMC DCT are discussed.