Piston-temperature measuring system using electromagnetic induction with verification by a telemetry system

The development of an inner-piston-chamber temperature measurement system is a necessary step in engine development or when solving other fundamental problems related to automotive engines. There are various pre-existing measurement methods available, e.g., the linkage method, piston telemetry, templog, and the electromagnetic induction method. In this study, we first redesigned the coil sensor used in the electromagnetic induction method using PEEK and then used Taguchi methods to reduce the number of experiments in the development process and finally utilized piston telemetry via Bluetooth to verify the precision and accuracy of the redesigned PEEK coil sensor and electromagnetic induction method. The results displayed a reproducibility within 0.5 degrees and an accuracy within 2 degrees Celsius.     

Parameter identification for a LuGre model based on steady-state tire conditions

The purpose of this study was to effectively identify parameters for a LuGre friction model based on experimental measures. In earlier work related to this study (Yang et al., 2009), which was based on the characters of polygonal wear (Sueoka and Ryu, 1997), we showed a frictional vibration model for a mass on a moving belt. This model reflected lateral vibrations caused by velocity and toe-in angle. An important aspect of the present study is the improved friction model. A previous friction model, which divided the process into four parts, expressed the sable excited vibration well but failed to reflect the hysteresis loop change when vehicles accelerated or decelerated continuously. A LuGre friction model can solve this problem, but several model parameters must be obtained experimentally. We measured contact width and length of tires as vertical pressure changed; this provided a theoretical basis for apparent stiffness of a unit of tire tread. Based on tire data from Bakker E’s article in a SAE paper from 1987, we identified the Stribeck exponent and Stribeck velocity in LuGre. Then, the results were implemented in a vibration system that verified the rationality of the data.     

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.     

Engine performance and toxic gas analysis of biobutanol-blended gasoline as a vehicle fuel

A comprehensive study evaluating the performance of biobutanol-blended gasoline in passenger cars was conducted because biobutanol is considered a better biofuel than bioethanol as it has no water solubility and it has a higher caloric value, giving it a higher energy value. Several kinds of samples—suboctane gasoline, 8 volume percentage and 16 volume percentage biobutanol—blended gasoline, and a 10 volume percentage MTBE-blended market sample (as the oxygencontaining gasoline)-were tested to evaluate the engine performance in terms of the detergency of the intake valves and combustion chambers, power, emissions, and fuel efficiency. Additionally, the toxicity of the emissions from these biobutanolblended samples was tested in order to assess the viability of biobutanol as one of the competitive potential substitutes for MTBE as an oxygenator in the near future. The results show that biobutanol-blended gasoline samples had relatively better detergency, relatively higher power, and similar levels of emissions compared with those of MTBE-blended gasoline. Formaldehyde was emitted from all of the samples at almost the same levels and within the error range, whereas biobutanolblended gasoline samples emitted approximately three times the amount of acetaldehyde than did the suboctane gasoline. This study shows that biobutanol is one of the best alternative bioalcohol fuels for use in the near future.     

Quality evaluation of car window motors using sound quality metrics

In this paper, a method to establish a decision criterion to evaluate the quality of small window motors using sound quality (SQ) metrics is suggested. Although the sound level radiated from the motor is relatively small compared to other sounds in a car, the sound from an abnormal motor gives an uncomfortable feeling and the impression of abnormal operation, which can lead to customer complaints. To construct an objective decision criterion, the correlation between the SQ metrics and the subjective decision on the passing or failure of the motor were investigated. Four representative SQ metrics, viz., loudness, sharpness, roughness, and fluctuation strength, were calculated for the collected samples. It was observed that the loudness and roughness of the motor sample group classified as abnormal was higher than those of the normal motors. For a single figure rating for motor quality, an evaluation index for the motor sound was generated by combining the correlated SQ metrics with proper weightings. Evaluation results on the specimens that were not employed in generating the quality evaluation index showed a reasonable agreement with the subjective test at 73%. The suggested quality check method can replace the current subjective decision procedure to identify the faulty motors.     

Damper modeling for dynamic simulation of a large bus with MR damper

In this study, a large bus is tested to measure its dynamic response by the single-lane change test and the rapid stop test. A full car model is established by ADAMS/Car for computer simulation. For multibody modeling of a large bus, user-defined templates are used in the simulation. Simulation results of the single-lane change test and the rapid braking test are compared to the results of the physical experiments, in which several sensors are installed to measure the vehicle’s responses. The results obtained from the simulation show good agreement with the tests’ results. A dynamic model for the MR(magnetic-rheological) damper is also developed by employing the Magic Formula model, which is widely used in the nonlinear modeling of a tire. Bump simulation of a full car with the MR damper is carried out to verify the performance of the MR damper. The comparison of the simulation results obtained with the MR damper model to the results obtained with the traditional passive damper model showed improved response of the vehicle with the MR damper.     

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.     

The price of uncertainty in pavement infrastructure management planning: An integer programming approach

Currently there is a true dichotomy in the pavement maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, there are stochastic models, with the most popular class being based on the theory of Markov decision processes that are able to account for various sources of uncertainties observed in the real-world. In this paper, we present an integer programming-based alternative to account for these uncertainties. A critical feature of the proposed models is that they provide – a priori – probabilistic guarantees that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources of uncertainty. By construction of the models, we can easily determine the additional budget requirements when additional sources of uncertainty are considered, starting from a fully deterministic model. We have coined this additional budget requirement the price of uncertainty to distinguish from previous related work where additional budget requirements were studied due to parameter uncertainties in stochastic models. A numerical case study presents valuable insights into the price of uncertainty and shows that it can be large.     

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.