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The purpose of this paper is to demonstrate the impact of low- floor bus seating configuration, passenger load factor (PLF) and passenger characteristics on individual boarding and disembarking (B-D) times -a key component of vehicle dwell time and overall transit system performance. A laboratory study was conducted using a static full-scale mock-up of a low-floor bus. Users of wheeled mobility devices (n=48) and walking aids (n=22), and visually impaired (n=17) and able-bodied (n=17) users evaluated three bus layout configurations at two PLF levels yielding information on B-D performance. Statistical regression models of B-D times helped quantify relative contributions of layout, PLF, and user characteristics viz., impairment type, power grip strength, and speed of ambulation or wheelchair propulsion. Wheeled mobility device users, and individuals with lower grip strength and slower speed were impacted greater by vehicle design resulting in increased dwell time.

A pioneering approach to implement transfer path analysis (TPA) is proposed in this paper through applying it to an automobile. We propose to use particle velocity as a measure of TPA, in addition to using sound pressure as a conventional measure for TPA. These two quantities together will give a comprehensive and complete definition of sound. Although sound pressure is a scalar, while particle velocity is a vector, it is also proposed that the same technique of the conventional sound pressure TPA should be independently applicable to each component of particle velocity vector. This has been experimentally verified with a study on our test box system. In this paper, we apply the proposed TPA to an actual vehicle to examine its applicability, advantages and limitations. The driving motor sound of a hybrid electric vehicle is chosen as the case study. A tri-axial particle velocity sensor which also measures sound pressure at the same point is utilized in the experiment.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Exhaust Gas Recirculation (EGR) coolers are commonly used in on-road and off-road diesel engines to reduce the recirculated gas temperature in order to reduce NOx emissions. One of the common performance behaviors for EGR coolers in use on diesel engines is a reduction of the heat exchanger effectiveness, mainly due to particulate matter (PM) deposition and condensation of hydrocarbons (HC) from the diesel exhaust on the inside walls of the EGR cooler. According to previous studies, typically, the effectiveness decreases rapidly initially, then asymptotically stabilizes over time. Prior work has postulated a deposit removal mechanism to explain this stabilization phenomenon. In the present study, five field aged EGR cooler samples that were used on construction machines for over 10,000 hours were analyzed in order to understand the deposit structure as well as the deposit composition after long duration use.

With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

Design of military vehicle needs to meet often conflicting requirements such as high mobility, excellent fuel efficiency and survivability, with acceptable cost. In order to reduce the development cost, time and associated risk, as many of the design questions as possible need to be addressed with advanced simulation tools. This paper describes a methodology to design a fuel efficient powerpack unit for a series hybrid electric military vehicle, with emphasis on the e-machine design. The proposed methodology builds on previously published Finite element based analysis to capture basic design features of the generator with three variables, and couples it with a model reduction technique to rapidly re-design the generator with desired fidelity. The generator is mated to an off the shelf engine to form a powerpack, which is subsequently evaluated over a representative military drive cycles.

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

A GT-SUITE vehicle-aftertreatment model has been developed to examine the cold-start emissions reduction capabilities of a Vacuum Insulated Catalytic Converter (VICC). This converter features a thermal management system to maintain the catalyst monolith above its light-off temperature between trips so that most of a vehicle’s cold-start exhaust emissions are avoided. The VICC thermal management system uses vacuum insulation around the monoliths. To further boost its heat retention capacity, a metal phase-change material (PCM) is packaged between the monoliths and vacuum insulation. To prevent overheating of the converter during periods of long, heavy engine use, a few grams of metal hydride charged with hydrogen are attached to the hot side of the vacuum insulation. The GT-SUITE model successfully incorporated the transient heat transfer effects of the PCM using the effective heat capacity method.

Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications-based information, is difficult and error-prone.

Growing environmental concerns and stringent vehicle emissions regulations has created an urge in the automotive industry to move towards electrified propulsion systems. Reducing and eliminating the emission from public transportation vehicles plays a major role in contributing towards lowering the emission level. Battery electric buses are regarded as a type of promising green mass transportation as they provide the advantage of less greenhouse gas emissions per passenger. However, the electric bus faces a problem of limited range and is not able to drive throughout the day without being recharged. This research studies a public bus transit system example which servicing the city of Ann Arbor in Michigan and investigates the impact of different electrification levels on the final CO2 reduction. Utilizing models of a conventional diesel, hybrid electric, and battery electric bus, the CO2 emission for each type of transportation bus is estimated.

The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance.

We have developed a system for automatic deceleration upon entering curves to prevent collisions on tight curves on high-ways. The navigation system is used to determine safe speed negotiating the curve, defined as a speed that will keep lateral acceleration within a settled value. The navigation system sends the curve radius to a controller, which calculates the safe speed for the curve. The controller then sends the speed command to the ACC system, which adjusts the vehicle speed. One of the important features in this system is the estimation of the vehicle position, in terms of its distance from the curve entrance. Navigation systems have a certain amount of dispersion in positional accuracy. A front camera is used in our system to decrease this dispersion. This camera detects lane markers (white lines, raised pavement markers, etc.) using our line recognition technologies1).

This simulation study explores the potential synergy between the HCCI engine system and three hybrid electric vehicle (HEV) configurations, and proposes the supervisory control strategy that maximizes the benefits of combining these two technologies. HCCI operation significantly improves fuel efficiency at part load, while hybridization aims to reduce low load/low speed operation. Therefore, a key question arises: are the effects of these two technologies additive or overlapping? The HEV configurations include two parallel hybrids with varying degrees of electrification, e.g. with a 5kW integrated starter/motor (“Mild”) and with a 10 kW electric machine (“Medium”), and a power-split hybrid. The engine is a dual-mode, SI-HCCI system and the engine map reflects the impact of HCCI on brake specific fuel consumption.

Electrification and hybridization have great potential for improving fuel economy and reducing visual signature or soot emissions in military vehicles. Specific challenges related to military applications include severe duty cycles, large and uncertain energy flows through the system and high thermal loads. A novel supervisory control strategy is proposed to simultaneously mitigate severe engine transients and to reduce high electric current in the battery without oversizing the battery. The described objectives are accomplished by splitting the propulsion power demand through filtering in the frequency domain. The engine covers only low frequency power demand profile while the battery covers high frequency components. In the proposed strategy, the separation filter is systematically designed to identify different frequency components with the consideration of fuel consumption, aggressive engine transients, and battery electric loads.

Suspension design is influenced by many factors, especially by vehicle dynamics performance in ride, handling and durability. In the global automotive industry it is common to “customize” or tune suspension parameters so that a vehicle is more acceptable to a different customer base and in a different driving environment. This paper seeks to objectively quantify certain aspects of tuning via ride optimization, taking account of market differences in road surface spectral properties and loading conditions. A computationally efficient methodology for suspension optimization is developed using stochastic techniques. A small (B-class) vehicle is chosen for the study and the following main suspension parameters are selected for optimization - spring stiffness, damping rate and vertical tire stiffness. The road is characterized as a stationary random process, using scaling and shaping filters representative of comparable roads in India and the USA.

The role of automotive electronics in light duty vehicles is continuing to expand rapidly. In this paper an overview of a 1986 Delphi forecast of major trends is presented. Trends discussed include electronics as a fraction of vehicle and component cost and projections of basic vehicle features supported by electronic technology. In addition, basic trends in diagnostics and multiplexing are presented. Several issues in support of automotive electronics are discussed, including the systems approach to vehicle engineering, the importance of developing a proper market strategy, and the continued major role of energy economics. The Delphi forecasting technique and its governing concepts are reviewed as a method to predict the future of automotive technology.

Chassis back and forth oscillation caused by sudden engine torque increase tends to occur, according to the characteristic of vehicle dynamics. This oscillation is called an acceleration surge and gives a vehicle driver a feeling of discomfort. This paper provides two control methods which can change the characteristic of vehicle acceleration response in order to suppress acceleration surge and to macth with driver's preference. The first control method is an acceleration servo method which is composed of control reference model and ignition timing control. The second control method is a variable response characteristic control algorithm. We treat the controlled object as the second order model with time delay, and assign the characteristic roots of transfer function in order to obtain the desired response.

Suspension is an important chassis part which is vital to ride comfort [1]. However, it is difficult to achieve our targeted comfortability level in a short time. Therefore, improving efficiency of damper development is our primary challenge. We have launched a project which aims to reduce the workload on developing dampers by introducing analytical approaches to the improvement of ride comfort. To be more specific, we have been putting effort into developing the damping force prediction, the vehicle dynamics prediction and subjective rating prediction. This paper describes subjective rating prediction method which output a subjective rating corresponding to the physical value of the vehicle dynamics with deep learning. As a result of verification using objective data which was not used for learning process, DNN (Deep Neural Network) prediction method could fairly precisely predict subjective rating of the expert driver.

We propose a combined battery system (CBS) for low cost electric vehicles (EVs) to enhance battery life. The EVs popularly called as Neighborhood Electric Vehicle or Low-Speed-Electric-Vehicle are spreading in developing countries. Conventionally the EVs batteries consist of high energy density cells, and we call it as energy cells (EC). A major issue with the EVs is high operational costs mainly due to high battery cost and short lifespan of the ECs. In this study, we develop a CBS consisting of a combination of following two kinds of batteries: i) EC which is the main energy source for the EV, and ii) a battery having high power density also called as power cells (PC) which is more suitable to bear high charge-discharge currents. The key feature of the proposed system is to minimize the size of additional battery by using our high power lithium ion battery. We performed experiments to estimate EC life for several capacity values of the PC.

The global energy situation, the dependence of the transportation sector on fossil fuels, and a need for rapid response to the global warming challenge, provide a strong impetus for development of fuel efficient vehicle propulsion. The task is particularly challenging in the case of trucks due to severe weight/size constraints. Hybridization is the only approach offering significant breakthroughs in near and mid-term. In particular, the series configuration decouples the engine from the wheels and allows full flexibility in controlling the engine operation, while the hydraulic energy conversion and storage provides exceptional power density and efficiency. The challenge stems from a relatively low energy density of the hydraulic accumulator, and this provides part of the motivation for a simulation-based approach to development of the system power management. The vehicle is based on the HMMWV platform, a 4×4 off-road truck weighing 5112 kg.