Performance optimization of CVT for two-wheeled vehicles

Continuously Variable Transmission (CVT) is one of the most promising automotive transmission technologies because of its continuously variable gear ratio and reduced shift shock. CVT is different from Manual Transmission and Automatic Transmission, and it is possible to operate the power source in its high efficiency region with CVT in the drive train. Several types of CVT exist that can be categorized based on the mechanism of power transmission, such as the belt pulley, traction drive, and hydrostatic types. This paper investigates the belt pulley CVT, which consists of a thrust actuator, driver pulley, belt, driven pulley, and preload spring of the output shaft. A complete CVT is constructed, and based on that a simulation program that analyzes the static performance of a CVT is implemented in Matlab/Simulink. From these simulation results, methods for improving the efficiency of the CVT are discussed. The coefficient of the torque capacity factor is proposed as affecting the matching between a power source and a CVT, and methods for improving the matching effect are also investigated.     

Effect of fuel stratification on initial flame development: Part 3-high swirl condition

This paper discusses the final investigation into the effect of fuel stratification on flame propagation. In previous works, the characteristics under the no port-generated swirl condition and the low-swirl condition were considered. For this purpose, the initial flame development and propagation were visualized under different axially stratified states in a modified optical single-cylinder SI engine. The images were captured by an intensified CCD camera through the quartz window mounted in the piston. Stratification was controlled by the combination of the port swirl ratio and injection timing. These were averaged and processed to characterize the flame propagation. The flame stability was estimated by the weighted average of flame area and luminosity. The stability was also evaluated through the standard deviation of flame area and propagation distance and through the mean absolute deviation of the propagation direction. The results show that the LML is expanded remarkably under the high-swirl cases up to the highest relative AFRs of 1.71 and 1.75 between 140 and 160CA. In addition, similar to the low-swirl condition, the flame-flow interaction determines the direction of flame propagation, and the governing roles of the two factors vary according to the swirl level; the flow is more important at the higher swirl conditions, and the flame is more important at the lower swirl condition. Finally, fast and stable flame propagation can be achieved under the preferably stratified condition, which is induced by the suitable combination of the high swirl and injection timing.     

Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.     

Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies

This paper reviews trends in cycling levels, safety, and policies in Canada and the USA over the past two decades. We analyze aggregate data for the two countries as well as city-specific case study data for nine large cities (Chicago, Minneapolis, Montréal, New York, Portland, San Francisco, Toronto, Vancouver, and Washington). Cycling levels have increased in both the USA and Canada, while cyclist fatalities have fallen. There is much spatial variation and socioeconomic inequality in cycling rates. The bike share of work commuters is more than twice as high in Canada as in the USA, and is higher in the western parts of both countries. Cycling is concentrated in central cities, especially near universities and in gentrified neighborhoods near the city center. Almost all the growth in cycling in the USA has been among men between 25-64 years old, while cycling rates have remained steady among women and fallen sharply for children. Cycling rates have risen much faster in the nine case study cities than in their countries as a whole, at least doubling in all the cities since 1990. They have implemented a wide range of infrastructure and programs to promote cycling and increase cycling safety: expanded and improved bike lanes and paths, traffic calming, parking, bike-transit integration, bike sharing, training programs, and promotional events. We describe the specific accomplishments of the nine case study cities, focusing on each city’s innovations and lessons for other cities trying to increase cycling. Portland’s comprehensive package of cycling policies has succeeded in raising cycling levels 6-fold and provides an example that other North American cities can follow.     

Timetable-based operation in urban transport: Run-time optimisation and improvements in the operating process

Urban public transit provides an efficient means of mobility and helps support social development and environmental preservation. To avoid loss of ridership, transit authorities have focussed on improving the punctuality of routes that operate using timetables. This paper presents a new approach to generating run-time values that is based on analytical development and micro simulations. The work utilizes previous research (described herein) and the experience acquired by Transports Metropolitans de Barcelona (TMB) in operating bus routes based on timetables. Using a sample of historical data, the method used for generating run-time values consists of the following steps: purging and screening atypical trips, based on the consideration of confidence intervals for median trips; segmenting the day into time bands based on the introduction of a new hierarchical classification algorithm; creating initial run-time values based on criteria derived from statistical analysis; adjusting and validating initial run-time values using micro simulations; and evaluating incident-recovery times at the end of trips in order to guarantee the punctual departure of the next trip in the vehicle schedule. To favour service improvement, we also introduced certain indicators that can identify the root causes of non-compliance. As a final step, in order to ensure the applicability and use of the model, we promoted the development of our model within the framework of the HASTUS™ software solution.     

Seaport research: A structured literature review on methodological issues since the 1980s

This study aims to investigate how seaport research has been conducted from the methodological perspective. To this end, this study reviews published port literature for the last three decades (1980-2000s). The investigation primarily categorises the literature according to various methodological issues such as research paradigm, research strategy, base-disciplines, research methods and analysis techniques in order to provide meaningful implications on methodological evolution in seaport research for the period. This study suggests methodological bias in port research to a positivistic paradigm, following a quantitative trajectory moving from conceptual to empirical studies. In addition, the increased use of mathematical modelling and advanced statistical analysis methods is clearly observed. The introduction of advanced analytical tools used in other academic disciplines facilitates discussions in particular research area and amplifies the literature in those areas. This paper also suggests research gaps from the methodological perspective and implications for future port research.     

Railway wheel-flat detection and measurement by ultrasound

This work presents an innovative ultrasound technique designed to detect and quantify flats formed in the rolling surface of railway wheels. Differently from other approaches, ultrasonic pulses (Rayleigh waves) are sent over a measuring rail. The variations in the round-trip time of flight (RTOF) of the ultrasound pulse to the rail-wheel contact point allow detecting and quantifying the wheel-flats. In spite of the wear state of the irregularity, the method provides the loss of material and the length of the flat originally formed by abrasion. A theoretical background supports the technique which offers many advantages for railway maintenance. Simulations and experimental results match the expected ones.     

A network option portfolio management framework for adaptive transportation planning

A real option portfolio management framework is proposed to make use of an adaptive network design problem developed using stochastic dynamic programming methodologies. The framework is extended from Smit’s and Trigeorgis’ option portfolio framework to incorporate network synergies. The adaptive planning framework is defined and tested on a case study with time series origin-destination demand data. Historically, OD time series data is costly to obtain, and there has not been much need for it because most transportation models use a single time-invariant estimate based on deterministic forecasting of demand. Despite the high cost and institutional barriers of obtaining abundant OD time series data, we illustrate how having higher fidelity data along with an adaptive planning framework can result in a number of improved management strategies. An insertion heuristic is adopted to run the lower bound adaptive network design problem for a coarse Iran network with 834 nodes, 1121 links, and 10 years of time series data for 71,795 OD pairs.     

Mobility, social exclusion and well-being: Exploring the links

Building on a growing research foundation, transport policy makers have begun to associate the ability to be mobile with having a role in the facilitation of social inclusion. However, the further connection to well-being is not as well understood. This paper explores the association between a person’s travel patterns, their risk of social exclusion and self-assessed well-being. Key influences on social exclusion are discussed, with trip making emerging as a significant influence. Trip making is not a significant direct influence on well-being but does exercise an indirect influence through the impact on risk of social exclusion. The modelling process enables a value for additional trips to be estimated, the value being about four times the values derived from conventional generated traffic approaches. Similar high values are found in separate metropolitan and regional case studies, confirming the significance of the results.     

GPS-based optimization of plug-in hybrid electric vehicles’ power demands in a cold weather city

Using the WPG03 duty cycle developed from global positioning data collected in Winnipeg, Canada, real world energy demands and costs are modeled. Three types of plug-in hybrid electric vehicles, four temperatures and two charging scenarios are compared to a vehicle with an internal combustion engine. Cold temperatures are shown to greatly affect vehicle operation energy costs, which is an important consideration for cold weather cities such as Winnipeg. The largest energy cost savings are obtained for smaller-battery plug-in hybrids that had the opportunity to charge during the day.