Analysis of planetary gear hybrid powertrain system part 2: Output split system

In recent studies, various types of multi-mode electric variable transmissions for hybrid electric vehicles have been proposed. A multi-mode electric variable transmission consists of two or more different types of a planetary gear hybrid powertrain system (PGHP), which can change power flow type using clutches to improve transmission efficiency. Input split systems are generally used for the single-mode powertrain because of their overall superiority, but other power split systems such as output split and compound split systems can be used in the dual-mode powertrain. In this study, we analyze the power transmission characteristics of output split systems, and evaluate their fuel economies in the FTP72 cycle, acceleration performance, and constant vehicle speeds. These results enable the selection of appropriate systems for a dual-mode powertrain.     

Development of the Inner Spherical CVT for a motorcycle

An Inner Spherical CVT (ISCVT) transfers engine power by utilizing the traction force of the lubricant fluid film on the contact point between concave and convex spherical rolling bodies. Since the concave and the convex contact surfaces of the ISCVT are exactly spherical parts, they have a large circular (not elliptic) contact area, and the ISCVT mechanism has a larger torque capacity, less spin loss, and better stability than other traction drive mechanisms. The IVT (Infinitely Variable Transmission) performances also can easily be embodied in the ISCVT. In this work, we developed a prototype of the ISCVT for a motorcycle with a 125cc single cylinder engine having a maximum torque of 13.73 Nm at 8,000 rpm. The design parameters were determined, and the transmission performances were evaluated by optimal design procedure. The transmission efficiency, the life time, the maximum severe stresses on each part of the ISCVT, and the work needed for varying speed ratio were theoretically investigated, and the efficiency performances were experimentally measured. The manufactured prototype was installed in an actual motorcycle, which was fixed on the test-bench equipped with a dynamometer. The parasitic loss of the prototype and the cross-sectional road load performance were tested. The power efficiency of the simulated prototype was between 87∼92%, and the life span was more than 50,000 hours. The tested overall power efficiency was around 70∼92% under frequent driving conditions, which is an impressive performance in a motorcycle transmission despite the small difference from the simulation.     

Strategies for improving the mode transition in a sequential parallel turbocharged automotive diesel engine

Parallel sequential turbocharging systems are able to operate in different modes, which are defined according to the turbochargers that simultaneously boost the engine, and are controlled by means of specific valves. In order to cover the full engine operating range, a smooth transition between turbocharging operating modes must be ensured. However, important disturbances affect both boost and exhaust pressure when shifting the operation mode, thus causing non-negligible torque oscillations. This paper presents different methods for smoothing such undesirable effects during mode transition. Strategies covering optimal synchronization of the control valves, control of the valves’ position, and correction of the injected fuel during the transition are analysed. A fully instrumented passenger car engine is used for illustrating the different torque smoothing methods, and experimental results for transitions during both steady operation and engine accelerations are shown.     

Development of a knowledge-based hybrid failure diagnosis system for urban transit

Urban transit is a complex system that contains both electrical and mechanical entities; therefore, it is necessary to construct a maintenance system for ensuring safety during high-speed driving. Expert systems are computer programs that use numerical or non-numerical domain-specific knowledge to solve problems. This research aims to develop an expert system that diagnoses the causes of failures quickly and displays measures to correct them. For the development of this expert system, the standardization of a failure code classification and the creation of a Bill of Materials (BOM) were first performed. Through the analysis of both failure history and maintenance manuals, a knowledge base has been constructed. Also, for retrieving the procedure of failure diagnosis and repair linking with the knowledge base, we have built a Rule-Based Reasoning (RRB) engine with a pattern matching technique and a Case-Based Reasoning (CBR) engine with a similar search method. Finally, this system has been developed as web based in order to maximize accessibility.     

Asking the right questions about telecommuting: Avoiding pitfalls in surveying homebased work

In designing travel behavior surveys, the problem is to define “work,” “home,” and similar words that are commonly used in our language but which have acquired a plethora of associated meanings. The difficulty has not been resolved by the many new terms coined to describe non-traditional ways to work. Such words as “telecommuting,” “teleworking,” “at-home work,” “hoteling,” “homebased business,” “road warriors” and “mobile workers,” lack any agreed-upon definitions yet they are used in common parlance as if they did. These new workstyles are of interest to travel planners because they may involve trip reduction. To forecast just how much trip reduction will occur, behavior needs to be measured by objective criteria. To avoid definitional traps, we recommend phrasing questions in terms of measurable variables such as the place of work and the time in days and hours spent at each location. That approach leaves researchers the option of applying their own definitions that fit the context of their analyses. Thus, rather than ask “How many days a week do you telecommute?” the more precise question can be asked: “How many days last week did you work at home instead of going to your usual work location?” This approach has the advantage that information gathered over years can be used unambiguously in various contexts. Definitions can be applied at the point of analysis. This paper illustrates errors and confusion that can arise from casually worded surveys using examples from private and public surveys. The author proposes a set of core questions with four levels of priority for consideration in designing future surveys of travel behavior.     

Optimal shipment decisions for an airfreight forwarder: Formulation and solution methods

We study the freight forwarder’s shipment planning problem in an airfreight forwarding network where a set of cargo shipments have to be transported to given destinations. We provide mixed integer programming formulations that use piecewise-linear cargo rates and account for volume and weight constraints, flight departure/arrival times, as well as shipment-ready times.After exploring the solution of such models using CPLEX, we devise two solution methodologies to handle large problem sizes. The first is based on Lagrangian relaxation, where the problems decompose into a set of knapsack problems and a set of network flow problems. The second is a local branching heuristic that combines branching ideas and local search. The two approaches show promising results in providing good quality heuristic solutions within reasonable computational times, for difficult and large shipment consolidation problems.     

An empirical analysis of freight transport traffic modes in Brazil, 1996–2012

This paper analyses the performance of freight transportation modes in Brazil – namely air, water, rail and road – from February 1996 to August 2012 by investigating their long memory properties using fractional integration and autoregressive models on monthly tonnage data. Two important features are analysed: the degree of dependence of transportation traffic across time and its seasonal structure over the period. Furthermore, the stability of parameters across the sample period is investigated, incorporating potential structural breaks in the data, which describe discontinuity in freight transportation traffic. Some policy implications are derived.     

Co-operation and competition in international container transport: strategies for ports

This paper focuses on the response of port authorities to the changing market environment in which they operate. It documents the changes taking place in the relationships between port authorities and terminal management companies and considers the strategic issues faced by these groups and other port interests. In particular, it investigates the potential conflicts of interest for a port authority in matters related to the level of competition amongst terminals within a port and the amount of competition amongst ports.     

Bayesian committee of neural networks to predict travel times with confidence intervals

Short-term prediction of travel time is one of the central topics in current transportation research and practice. Among the more successful travel time prediction approaches are neural networks and combined prediction models (a ‘committee’). However, both approaches have disadvantages. Usually many candidate neural networks are trained and the best performing one is selected. However, it is difficult and arbitrary to select the optimal network. In committee approaches a principled and mathematically sound framework to combine travel time predictions is lacking. This paper overcomes the drawbacks of both approaches by combining neural networks in a committee using Bayesian inference theory. An ‘evidence’ factor can be calculated for each model, which can be used as a stopping criterion during training, and as a tool to select and combine different neural networks. Along with higher prediction accuracy, this approach allows for accurate estimation of confidence intervals for the predictions. When comparing the committee predictions to single neural network predictions on the A12 motorway in the Netherlands it is concluded that the approach indeed leads to improved travel time prediction accuracy.