Switch Panel wear loading – a parametric study regarding governing train operational factors

The acting forces and resulting material degradation at the running surfaces of wheels and rail are determined by vehicle, track, interface and operational characteristics. To effectively manage the experienced wear, plastic deformation and crack development at wheels and rail, the interaction between vehicle and track demands a system approach both in maintenance and in design. This requires insight into the impact of train operational parameters on rail- and wheel degradation, in particular at switches and crossings due to the complex dynamic behaviour of a railway vehicle at a turnout. A parametric study was carried out by means of vehicle-track simulations within the VAMPIRE® multibody simulation software, performing a sensitivity analysis regarding operational factors and their impact on expected switch panel wear loading. Additionally, theoretical concepts were cross-checked with operational practices by means of a case study in response to a dramatic change in lateral rail wear development at specific switches in Dutch track. Data from train operation, track maintenance and track inspection were analysed, providing further insight into the operational dependencies. From the simulations performed in this study, it was found that switch rail lateral wear loading at the diverging route of a 1:9 type turnout is significantly influenced by the level of wheel–rail friction and to a lesser extent by the direction of travel (facing or trailing). The influence of other investigated parameters, being vehicle speed, traction, gauge widening and track layout is found to be small. Findings from the case study further confirm the simulation outcome. This research clearly demonstrates the contribution flange lubrication can have in preventing abnormal lateral wear at locations where the wheel–rail interface is heavily loaded.     

Design and development of automotive blind spot detection radar system based on ROI pre-processing scheme

In the conventional 2D-FFT based target detection method, all range-Doppler cells are computed by FFT (Fast Fourier Transform) and scanned by CA-CFAR (Cell-Averaging Constant False Alarm Rate) detection. This results in high computational complexity and long processing time. In this paper, we developed an automotive 24 GHz BSD (Blind Spot Detection) FMCW (Frequency Modulated Continuous Wave) radar with a low complexity target detection architecture based on a ROI (Region Of Interest) pre-processing scheme. In the real BSD zone, because the number of cars to be detected is limited, the designed method only extracts their velocities corresponding to the range ROIs in which real targets exist. Moreover, the presence probability of vehicles with the same range-bin but different velocities is very low. Thus, in the designed method, some Doppler ROIs cells with a high magnitude are only applied for CA-CFAR detection. This architecture can dramatically reduce the amount of data to be processed compared to that of the conventional 2D FFT based method, resulting in enhanced processing time. We developed a 24 GHz FMCW radar system composed a transceiver, antennas, and signal processing module. The designed algorithm was implemented in a tiny micro-processor of the signal processing module. By implementing our proposed algorithm in the developed 24 GHz FMCW radar system in an anechoic chamber and a real road, we verified that the range and velocity of a car occupying the BSD zone were detected. Compared to that of the conventional method, the reduction ratio of the total processing time was measured to be 52.4 %.     

Experimental study on performance characteristics of cold storage heat exchanger for ISG vehicle

The ISG (Idle Stop and Go) system isvery useful in the automobile industry because it increases fuel consumption and reduces green house gas emissions. However, when the engine is on standby, the air-conditioning system does not work due to compressor inactivity, causing thermal discomfort to passengers. This study examines the thermal storage system, which is a cold storage heat exchanger integrated with a current evaporator. The experiments were conducted for an optimum cold storage heat exchanger design with various fin heights and densities, a number of stacking evaporator plates, refrigerant flow circuits inside the evaporator, and PCMs (Phase Change Materials) in the heat exchanger. The effects of coldness-release performance were examined with various ambient temperatures and air flow volume rates to the cold storage heat exchanger. The visualization of PCM’s freezing and melting was conducted with the cold storage heat exchanger. From the results, we found that the air discharge temperature of the air-conditioning system that was applied to the optimum cold storage heat exchanger was delayed around 540 seconds compared to the current air-conditioning system to reach 24 °C. Thus we can say that the cold storage heat exchanger integrated with an evaporator is an effective solution for ISG vehicles in maintaining thermal comfort in vehicle cabins during short engine stops.     

采用自动识别系统对水下输气管线、离岸平台和船舶检验评分的实时监测（英文）

The aim of this research is to develop an algorithm and application that can perform real-time monitoring of the safety operation of offshore platforms and subsea gas pipelines as well as determine the need for ship inspection using data obtained from automatic identification system(AIS). The research also focuses on the integration of shipping database,AIS data, and others to develop a prototype for designing a real-time monitoring system of offshore platforms and pipelines. A simple concept is used in the development of this prototype, which is achieved by using an overlaying map that outlines the coordinates of the offshore platform and subsea gas pipeline with the ship's coordinates(longitude/latitude) as detected by AIS. Using such information, we can then build an early warning system(EWS) relayed through short message service(SMS), email, or other means when the ship enters the restricted and exclusion zone of platforms and pipelines. The ship inspection system is developed by combining several attributes. Then, decision analysis software is employed to prioritize the vessel's four attributes, including ship age, ship type, classification, and flag state.Results show that the EWS can increase the safety level of offshore platforms and pipelines, as well as the efficient use of patrol boats in monitoring the safety of the facilities. Meanwhile, ship inspection enables the port to prioritize the ship to be inspected in accordance with the priority ranking inspection score.     

Open-type ferry safety system design for using LNG fuel

In this feasibility study, we investigate the viability of using Liquefied Natural Gas (LNG) fuel in an open type Ro-Ro passenger ferry and the associated potential challenges with regard to the vessel safety systems. We recommend an appropriate methodology for converting existing ships to run on LNG fuel, discuss all the necessary modifications to the ship’s safety systems, and also evaluate the relevant ship evacuation procedures. We outline the basic requirements with which the ship already complies for each safety system and analyze the additional restrictions that must be taken into consideration for the use of LNG fuel. Appropriate actions are recommended. Furthermore, we carry out a hazard identification study. Overall, we clearly demonstrate the technical feasibility of the investigated scenario. Minimal modifications to the ship’s safety systems are required to comply with existing safety rules for this specific type of ship.     

Decision fusion of a multi-sensing embedded system for occupant safety measures

The need for an embedded system that can fuse incomplete, inconsistent, and imprecise decisions from several sensing systems is a crucial step in achieving an effective decision for occupant safety measures. This paper deals with the decision fusion strategies of a multi-sensing embedded system to achieve significant enhancement in the reliability of occupant safety through the fused decisions. Multi-sensing approaches to determine weight, vision, and crash sensing are developed for occupant detection, classification, position calculation, and crash detection. A rule-based decision fusion algorithm is then developed to fuse the multi-sensing decisions. The developed sensing systems are incorporated into an embedded device. To execute the embedded system, a system interface between the software and hardware is developed using Lab Window/CVI with the C programming language. The experimental results demonstrated that the real time operation of the embedded system validate the effectiveness of the decision fusion algorithm, characterize the safety measures and monitor the decision application. Several events were tested that prove the performance of the embedded system is robust towards occupant safety measures.     

Numerical investigation of turbolag reduction in HD CNG engines by means of exhaust valve variable actuation and spark timing control

Turbocharging port-injected Natural Gas (NG) engines allows them to recover gaseous-fuel related power gap with respect to gasoline engines. However, turbolag reduction is necessary to achieve high performance during engine transient operations and to improve vehicle fun-to-drive characteristics. Significant support for the study of turbocharged Compressed Natural Gas (CNG) engines and guidelines for the turbo-matching process can be provided by 1-D numerical simulation tools. However, 1-D models are predictive only when a careful tuning procedure is set-up and carried out on the basis of the experimental data. In this paper, a 1-D model of a Heavy-Duty (HD) turbocharged CNG engine was set up in the GT-POWER (Gamma Technologies Inc., Westmont, IL, US) environment to simulate transient operations and to evaluate the turbolag. An extensive experimental activity was carried out to provide experimental data for model tuning. The model buildup and tuning processes are described in detail with specific reference to the turbocharger model, whose correct calibration is a key factor in accounting for the effects of turbine flow pulsations. The second part of the paper focuses on the evaluation of different strategies for turbolag reduction, namely, exhaust valve variable actuation and spark timing control. Such strategies were aimed at increasing the engine exhaust-gas power transferred to the turbine, thus reducing the time required to accelerate the turbocharger group. The effects of these strategies were examined for tip-in maneuvers at a fixed engine speed. Depending on the engine speed and the applied turbolag reduction strategy, turbolag reductions from 70% to 10% were achieved.     

Inclusion of latent variables in Mixed Logit models: Modelling and forecasting

Travel demand models typically use mainly objective modal attributes as explanatory variables. Nevertheless, it has been well known for many years that attitudes and perceptions also influence users’ behaviour. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of subjective factors. We estimated hybrid models in a short-survey panel context for data among many alternatives. The paper analyses the results of applying these models to a real urban case study, and also proposes an approach to forecasting using these models. Our results show that hybrid models are clearly superior to even highly flexible traditional models that ignore the effect of subjective attitudes and perceptions.     

A robust,data-driven methodology for real-world driving cycle development

This paper develops a robust, data-driven Markov Chain method to capture real-world behaviour in a driving cycle without deconstructing the raw velocity–time sequence. The accuracy of the driving cycles developed using this method was assessed on nine metrics as a function of the number of velocity states, driving cycle length and number of Markov repetitions. The road grade was introduced using vehicle specific power and a velocity penalty. The method was demonstrated on a corpus of 1180 km from a trial of electric scooters. The accuracies of the candidate driving cycles depended most strongly on the number of Markov repetitions. The best driving cycle used 135 velocity modes, was 500 s and captured the corpus behaviour to within 5% after 1,000,000 Markov repetitions. In general, the best driving cycle reproduced the corpus behaviour better when road grade was included.     

Investigation of hardware-in-the-loop for use in suspension development

Hardware-in-the-loop (HiL) is a testing method in which real-time measurements on physical hardware replace the mathematical model of the particular hardware during simulation. The development of a semi-active suspension prompted the need for such capability. HiL, implemented on a PC with a dSpace^TM board in conjunction with a hydrodynamic actuator, was compared to software simulations of single degree of freedom (DOF) and two DOF systems. HiL was also compared to a physical (ballast-based) two DOF system, comprising the rear suspension of a motorcycle. Comparisons between the HiL and software responses showed its suitability for testing suspension systems, thus providing a viable alternative to ballast-based suspension tests, using available hardware. The research also showed that actuator dynamics, filter types and amounts, and signal reference levels required special consideration.