Optimal design and benefits of a short turning strategy for a bus corridor

We develop a short turning model using demand information from station to station within a single bus line-single period setting, aimed at increasing the service frequency on the more loaded sections to deal with spatial concentration of demand considering both operators’ and users’ costs. We find analytical expressions for optimal values of the design variables, namely frequencies (inside and outside the short cycle), capacity of vehicles and the position of the short turn limit stations. These expressions are used to analyze the influence of different parameters in the final solution. The design variables and the corresponding cost components for operators and users (waiting and in-vehicle times) are compared against an optimized normal operation scheme (single frequency). Applications on actual transit corridors exhibiting different demand profiles are conducted, calculating the optimal values for the design variables and the resulting benefits for each case. Results show the typical demand configurations that are better served using a short turn strategy.     

On the macroscopic stability of freeway traffic

A simple model of traffic flow is used to analyze the spatio-temporal distribution of flow and density on closed-loop homogeneous freeways with many ramps, which produce inflows and allow outflows. As we would expect, if the on-ramp demand is space-independent then this distribution tends toward uniformity in space if the freeway is either: (i) uncongested; or (ii) congested with queues on its on-ramps and enough inflow to cause the average freeway density to increase with time. In all other cases, however, including any recovery phase of a rush hour where the freeway’s average density declines, the distribution of flow and density quickly becomes uneven. This happens even under conditions of perfect symmetry, where the percentage of vehicles exiting at every off ramp is the same. The flow-density deviations from the average are shown to grow exponentially in time and propagate backwards in space with a fixed wave speed. A consequence of this type of instability is that, during recovery, gaps of uncongested traffic will quickly appear in the unevenly congested stream, reducing average flow. This extends the duration of recovery and invariably creates clockwise hysteresis loops on scatter-plots of average system flow vs. density during any rush hour that oversaturates the freeway. All these effects are quantified with formulas and verified with simulations. Some have been observed in real networks. In a more practical vein, it is also shown that the negative effects of instability diminish (i.e., freeway flows increase) if (a) some drivers choose to exit the freeway prematurely when it is too congested and/or (b) freeway access is regulated in a certain traffic-responsive way. These two findings could be used to improve the algorithms behind VMS displays for driver guidance (finding a), and on-ramp metering rates (finding b).     

Data-driven State-of-Charge estimator for electric vehicles battery using robust extended Kalman filter

An accurate battery State-of-Charge (SoC) estimation method is one of the most significant and difficult techniques to promote the commercialization of electric vehicles. This paper tries to make two contributions to the existing literatures through a robust extended Kalman filter (REKF) algorithm. (1) An improved lumped parameter battery model has been proposed based on the Thevenin battery model and the global optimization-oriented genetic algorithm is used to get the optimal polarization time constant of the battery model. (2) A REKF algorithm is employed to build an accurate data-driven based robust SoC estimator for a LiFePO4 lithium-ion battery. The result with the Federal Urban Driving Schedules (FUDS) test shows that the improved lumped parameter battery model can simulate the dynamic performance of the battery accurately. More importantly, the REKF based SoC estimation approach makes the SoC estimation with high accuracy and reliability, it can efficiently eliminate the problem of accumulated calculation error and erroneous initial estimator state of the SoC.     

Automobile defrosting system analysis through a full-scale model

Adequate visibility through the automobile windshield is of paramount practical significance, most often at very low temperatures when ice tends to form on the windshield screen. But the numerical simulation of the defrost process is a challenging task because phase change is involved. In this study numerical solution was computed by a finite volume computational fluid dynamics (CFD) program and experimental investigations were performed to validate the numerical results. It was found that the airflow produced by the defrost nozzle is highly nonuniform in nature and does not cover the whole windshield area. The nonuniformity also severely affected the heating temperature pattern on the windshield. The windshield temperature reached a maximum in the vicinity of the defroster nozzle in the lower part of the windshield and ranged from 9∼31°C over a period of 30 min, which caused the frost to melt on the windshield. The melting time was under 10 minutes, which satisfied the NHTSA standard. The numerical predictions were in close agreement with the experimental results. Thus, CFD can be a very useful design tool for an automobile HVAC system.     

Automotive window seal design considering external aerodynamic load and surrogate constraint modeling

Installed between metallic DIW (Door in White) panel and nonmetallic door glass, automotive window seals has great influence on customers’ perception of NVH (Noise-Vibration-Harshness) performance. Recently, aerodynamic effect on ride comfort attracts increasing research interest. The external load causes unsteady pressure on glass, which is finally transferred to window seals and leads to complicated vibration and increases interior noise level. However, non-linearities of hyper-elastic material, rubber-glass contact and large deformation behavior make the construction of window seals constraint model much more difficult, thus impeding further analysis and optimization. A new window seal design method is proposed featuring in considering aerodynamics-induced load and nonlinear constraint. Firstly, by SST ? k ? ε (Shear Stress Transport) turbulence model, external flow field of full-scale automotive is established by solving three-dimensional, steady and uncompressible Navier-Stokes equation. With re-exploited mapping algorithm, the overall aerodynamic pressure is extracted and matched to local window as external loads for seals, thus taking into account high speed fluid-structure interaction. Secondly, based on functional equivalence and mathematical fitting, new surrogate constraint model is presented. The unitedseal CLD (Compression Load Deflection) curve is synthesized after translations and transformations from two semi-seal CLD experimental measurements of inner and outer lips. It is then fit to complex exponential function, making seal constraint equivalent to a surrogate elastic constraint with variable stiffness. Experiment is performed to verify the constraint surrogation effectiveness. Finally, case study of window seal design under high speed is investigated. After seal optimization based on the new method, windows seals’ maximal displacements have decreased. The improved seal-glass fitting status shows better NVH quality of window seal in high-speed condition.     

Railway vehicle performance optimisation using virtual homologation

Unlike regular automotive vehicles, which are designed to travel in different types of roads, railway vehicles travel mostly in the same route during their life cycle. To accept the operation of a railway vehicle in a particular network, a homologation process is required according to local standard regulations. In Europe, the standards EN 14363 and UIC 518, which are used for railway vehicle acceptance, require on-track tests and/or numerical simulations. An important advantage of using virtual homologation is the reduction of the high costs associated with on-track tests by studying the railway vehicle performance in different operation conditions. This work proposes a methodology for the improvement of railway vehicle design with the objective of its operation in selected railway tracks by using optimisation. The analyses required for the vehicle improvement are performed under control of the optimisation method global and local optimisation using direct search. To quantify the performance of the vehicle, a new objective function is proposed, which includes: a Dynamic Performance Index, defined as a weighted sum of the indices obtained from the virtual homologation process; the non-compensated acceleration, which is related to the operational velocity; and a penalty associated with cases where the vehicle presents an unacceptable dynamic behaviour according to the standards. Thus, the optimisation process intends not only to improve the quality of the vehicle in terms of running safety and ride quality, but also to increase the vehicle availability via the reduction of the time for a journey while ensuring its operational acceptance under the standards. The design variables include the suspension characteristics and the operational velocity of the vehicle, which are allowed to vary in an acceptable range of variation. The results of the optimisation lead to a global minimum of the objective function in which the suspensions characteristics of the vehicle are optimal for the track, the maximum operational velocity is increased while the safety and ride quality measures of the vehicle, as defined by homologation standards, are either maintained in acceptable values or improved.     

Fatigue features extraction of road load time data using the S-transform

This paper presents the algorithm development of a new fatigue data editing technique using S-T approach. In general, the S-transform (S-T) is a time-frequency spectral localization method which performs a multi-resolution analysis on signal. This method represents a better time-frequency resolution especially for non-stationary signal analysis. This technique was developed to produce shortened fatigue data for fatigue durability testing. The S-T method was applied to detect the damaging events contained in the fatigue signals due to high S-T spectrum location. The damaging events were extracted from an original fatigue signal to produce the shortened edited signal which has equivalent fatigue damage. Three types of road load fatigue data were used for simulation purpose, pave track, highway and country road. In this study, an algorithm was developed, to detect the damaging events in the original fatigue signal. The algorithm can be used to extract the fatigue damaging events and these events were combined in order to produce a new edited signal which neglect the low amplitude cycles. The edited signal consists of the majority of the original fatigue damage in the shortened signal with 15–25% time reduction. Thus, it has been suggested that this shortened signal can then be used in the laboratory fatigue testing for the purpose of accelerated fatigue testing.     

Low temperature premixed combustion within a small bore high speed direct injection (HSDI) optically accessible diesel engine using a retarded single injection

An optically accessible single-cylinder high speed direct-injection (HSDI) Diesel engine equipped with a Bosch common rail injection system was used to study low temperature Modulated Kinetics (MK) combustion with a retarded single main injection. High-speed liquid fuel Mie-scattering was employed to investigate the liquid distribution and evolution. By carefully setting up the optics, three-dimensional images of fuel spray were obtained from both the bottom of the piston and the side window. The NOx emissions were measured in the exhaust pipe. The influence of injection pressure and injection timing on liquid fuel evolution and combustion characteristics was studied under similar fuel quantities. Interesting spray development was seen from the side window images. Liquid impingement was found for all of the cases due to the small diameter of the piston bowl. The liquid fuel tip hits the bowl wall obliquely and spreads as a wall jet in the radial direction of the spray. Due to the bowl geometry, the fuel film moves back into the central part of the bowl, which enhances the air-fuel mixing process and prepares a more homogeneous air-fuel mixture. Stronger impingement was seen for high injection pressures. Injection timing had little effect on fuel impingement. No liquid fuel was seen before ignition, indicating premixed combustion for all the cases. High-speed combustion video was taken using the same frame rate. Ignition was seen to occur on or near the bowl wall in the vicinity of the spray tip, with the ignition delay being noticeably longer for lower injection pressure and later injection timing. The majority of the flame was confined to the bowl region throughout the combustion event. A more homogeneous and weaker flame was observed for higher injection pressures and later injection timing. The combustion structure also proves the mixing enhancement effect of the liquid fuel impingement. The results show that ultra-low sooting combustion is feasible in an HSDI diesel engine with a higher injection pressure, a higher EGR rate, or later injection timing, with little penalty on power output. It was also found that injection timing has more influence on HCCI-like combustion using a single main injection than the other two factors studied. Compared with the base cases, simultaneous reductions of soot and NOx were obtained by increasing EGR rate and retarding injection timing. By increasing injection pressure, NOx emissions were increased due to leaner and faster combustion with better air-fuel mixing. However, smoke emissions were significantly reduced with increased injection pressure.     

Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework

ABSTRACT

This paper is designed to evaluate and improve the effectiveness of transportation systems and reduce traffic congestion through the use of simulation models and scenario development. A system dynamics framework is used to test and evaluate the alternatives of future strategies for the city of Surabaya, Indonesia. Some factors affecting the effectiveness of transport systems include operational effectiveness and service effectiveness, as well as uncertainty. To improve the effectiveness of transportation systems, several strategies can be implemented, such as subsidizing public transportation, increasing the cost of private vehicle parking fees, raising taxes on private vehicles, and reducing delays in public transportation through scenario development. Scenario results show that, by pursuing these strategies, effectiveness could be improved by 80% as the impact of the increase in operational and service effectiveness, helping to mitigate traffic congestion. Congestion could be reduced to 70% (on average) due to the decrease in daily traffic.     

Effects of Human Activities on the World's Most Vulnerable Coral Reefs: Comoros Case Study

Effective management of highly biodiverse and threatened reefs requires the identification of human activities driving declines on the particular reef to be managed. The island nation of the Comoros is a model setting to investigate effects of human activities on diverse and threatened coral reefs, with abundant and diverse marine life, local dependence on reef resources, and a variety of anthropogenic pressures on reefs rendering the nation vulnerable to coral reef degradation. Using data from 21 sites throughout the Comoros, we evaluated the relative influence of human activities and other natural and anthropogenic factors on benthic cover and fish richness, abundance, and biomass with the goal of providing prioritized management targets. Human activities including fishing, beach sand extraction, and beachfront housing and development had the strongest relationship with degraded reefs but with some seasonal fluctuation, while geographic patterns most consistently predicted reef degradation across seasons. Comparing analyses conducted with and without human activities as predictors, the inclusion of human activities greatly improved explanatory power. Baseline data on reef biotic composition and localized anthropogenic impacts, monitoring over time, and controlled experiments can facilitate an adaptive management approach for protecting fragile reef ecosystems in the Comoros and elsewhere.