Influence of peak spreading and departure time choice on evaluation of its measures

Intelligent transport systems provide various means to improve capacity and travel time in road networks. Evaluation of the benefits of these improvements requires consideration of travellers' response to them. We consider a continuous‐time equilibrium model of departure time choice and identify a formula for the dynamic equilibrium departure rate profile. We develop the analysis to consider the effect on the cost incurred by travellers of ITS measures through their effects on each of the travel time in the absence of congestion, and the capacity for travel. This shows the importance in choice of departure time of travellers' values of time at each of the origin and destination of their journeys. We show the importance of these values of time in evaluation, and that if travellers value their time at both the origin and destination of their journeys, their responses will lead them to achieve a greater reduction in costs than would be achieved under free‐flow conditions.     

Validation of railway vehicle dynamic models in training simulators

Training simulators play an important role for sustaining safety, efficiency and cost effective railway transportation. Dynamic modelling of train systems is one of the main modules of training simulators. Validation of the dynamic models with collected real data ensures the fidelity of the simulator utilising the respective models. In this study, a validation process (Dynamic Modelling Validation Process (DyMVaP)) which is developed to support the validation of railway dynamic models is introduced. However, the proposed process can also be used in validating other dynamic models as well. The developed process is based on five steps including the preparation of validation scenarios, sensor deployment, real data collection, data preparation, and comparison of simulated and measured data. Note that the proposed DyMVaP was used for the validation of a full-mission training simulator so called TRENSIM, which was developed for Turkish State Railways. During the study it is realised that the current speed, travelled distance, acceleration (in x, y, z directions), rotation angles (around x, y, z axes), air pressure, in-train pressure/tension forces, traction motor currents, catenary voltage, positions of controllers must be collected synchronously by using proper sensors in order to ensure simulation validation. The required data was collected from locomotive body, bogies, wheel sets and connection of railway cars. The data (～200?GB) collected from the field by applying 27 different scenarios and transformed into appropriate data for utilising the generated dynamic models within the simulator. The measured and simulated data were also compared visually using graphical representation of the parameters as well as performing computations regarding the magnitude, phase and comprehensive error factors.     

Motion cueing in high-performance vehicle simulators

The majority of motion cueing algorithms have been developed for passenger car applications, with correspondingly less research dedicated to race-car and high-performance vehicle simulators. In the high-performance context, the focus is on cueing the vehicle's behavioural and handling characteristics, particularly when driving near the limits of performance. In race-car simulators the cueing requirements are therefore quite different, with the problem made all the more challenging by the presence of large accelerations. To understand the drivers' cueing needs, the vehicle's stability and handling response characteristics must be examined near the performance boundary. Frozen-time eigenvalue analyses are used to determine stability and response characteristics across all vehicle operating conditions, including accelerating and braking under cornering, with the results used to determine motion cueing algorithm requirements. Lateral acceleration and yaw cueing filters are designed in order to retain information critical to understanding the vehicle's behaviour on its performance boundary. Cueing filters are then tested, with the help of a professional race-car driver, and are found to provide the cues necessary for the driver to control the vehicle on the limit of performance.     

Experimental and 3D,embedded modeling for diesel engine SCR deposit

Nowadays, the selective catalytic reduction (SCR) is a promising solution to fulfill stringent nitrogen oxide (NO_X) emission standards enforced by worldwide regulation bodies for lean burning engines. However, in the practical operation, urea deposits occur under unfavorable conditions, which bring about a failure of urea dosing strategy, affect the SCR system de-NOx performance and lowering the fuel economy by increasing the engine back pressure. This paper will present 3D deposit model, which can be used to predict the deposit position. Furthermore, a model-based controls strategy and calibration are designed. The comparison test results of both engine emission tests and vehicle field tests shows there is significant deposits improvement with the embedded model.     

Emission-robust operation of diesel HEV considering transient emissions

In this paper, we consider a method to create an engine emission simulation model for cycle and customer driving of a vehicle. The emission model results from an empiric approach, also taking into account the effects of engine dynamics on emissions. We analysed transient engine emissions in driving cycles and during representative customer driving profiles and created emission meta models. The analysis showed a significantly higher correlation in emissions when simulating realistic customer driving profiles using the created verified meta models (< 1 % model error) compared to static approaches, which are commonly used for vehicle simulation. Therefore, a transient modelling approach is conducted, which shows a great increase in accuracy in customer driving operation.     

Novel stability control strategy for distributed drive electric vehicle based on driver operation intention

In this paper, a novel direct yaw control method based on driver operation intention for stability control of a distributed drive electric vehicle is proposed. It was discovered that the vehicle loses its stability easily under an emergency steering alignment (EA) problem. An emergent control algorithm is proposed to improve vehicle stability under such a condition. A driver operation intention recognition module is developed to identify the driving conditions. When the vehicle enters into an EA condition, the module can quickly identify it and transfer the control method from normal direct yaw control to emergency control. Two control algorithms are designed. The emergency control algorithm is applied to an EA condition while the adaptive control algorithm is applied to other conditions except the EA condition. Both simulation results and real vehicle results show that: The driver module can accurately identify driving conditions based on driver operation intention. When the vehicle enters into EA condition, the emergent control algorithm can intervene quickly, and it has proven to outperform normal direct yaw control for better stabilization of vehicles.     

Experimental investigations on continuous regenerative anti-lock braking system of full electric vehicle

Functions of anti-lock braking for full electric vehicles (EV) with individually controlled wheel drive can be realized through conventional brake system actuating friction brakes and regenerative brake system actuating electric motors. To analyze advantages and limitations of both variants of anti-lock braking systems (ABS), the presented study introduces results of experimental investigations obtained from proving ground tests of all-wheel drive EV. The brake performance is assessed for three different configurations: hydraulic ABS; regenerative ABS only on the front axle; blended hydraulic and regenerative ABS on the front axle and hydraulic ABS on the rear axle. The hydraulic ABS is based on a rule-based controller, and the continuous regenerative ABS uses the gain-scheduled proportional-integral direct slip control with feedforward and feedback control parts. The results of tests on low-friction road surface demonstrated that all the ABS configurations guarantee considerable reduction of the brake distance compared to the vehicle without ABS. In addition, braking manoeuvres with the regenerative ABS are characterized by accurate tracking of the reference wheel slip that results in less oscillatory time profile of the vehicle deceleration and, as consequence, in better driving comfort. The results of the presented experimental investigations can be used in the process of selection of ABS architecture for upcoming generations of full electric vehicles with individual wheel drive.     

Finite element damage analysis of an underwater glider–ship collision

Underwater gliders, which are profiling autonomous underwater vehicles designed to make oceanographic measurements, are increasingly used in the coastal ocean. As they regularly surface for data transmission, gliders increasingly pose a risk for fast ships. In order to estimate the extent of damage due to collision, 3D finite element simulations of collisions between a glider and a high-speed craft with a glass-fiber reinforced plastic hull are performed. Different collision scenarios such as impact locations, angles of attack and speeds are examined. The results are compared to an analytical solution based on simplifying assumptions. Although both methods reveal consistent results, it is shown that finite element simulations are required to account for the 3D shape of the ship. The results indicate that at ship velocities exceeding 7.5 m/s (14.6 kt) the glider penetrates the ship’s hull causing severe damage to its structure.     

特殊分段的精度控制方法探讨

在明确了分段精度控制意义及概念的前提下,对分段精度控制计划和精度控制管理过程作了详细分析,并制定相应的控制方法。首先针对舵臂分段,根据其尾部曲率较大以及不规则性,依据挂舵垂直性控制其精度;然后针对尾轴分段,根据同心度和尾轴管的定位控制该分段的精度;再针对主基座分段,主要根据基座面板水平度来控制该分段的精度;最后总结出典型分段精度控制方法。