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The pace of replacement of petroleum-based fuels as the primary fuel supply for transportation may still be a point of debate. However, the need to find a viable replacement fuel or group of fuels is no longer a major point of debate. The panel will outline what has changed on the journey during the past few years and what the future holds. Viewpoints from government, the military, fuel suppliers and academia will be presented.

This paper compares two different rule-based power management (PM) strategies, in terms of their resultant fuel consumptions, through a simulation study as applied to a hybrid hydraulic multi-actuator displacement controlled (DC) system. Presenter Rohit Hippalgaonkar

Advanced vehicular thermal management system can improve engine performance, minimize fuel consumption, and reduce emissions by harmoniously operating computer-controlled servomotor components. In this paper, a neural network-based optimal control strategy is proposed to regulate the engine temperature through the advanced cooling system. Presenter Asma Al Tamimi, Hashemite University

Concerned with fuel consumption and emissions, especially public transportation in urban areas, the ELFA electric drive system has been developed for hybrid bus applications. This modular system provides bus manufactures a cost effective solution with a maximum degree of design flexibility. Presenter Joshua Nelke, siemens industry inc.

Architecting and integrating commercial hybrid electric vehicles (HEV) is a long and labor intensive process which is unique every time. The challenge intensifies when one attempts to create an HEV capable of engine-off operation. Presenter Benjamin Saltsman, Eaton Corp.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. Presenter Chinmaya Patil, Eaton Corporation

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

Abstract This study investigates methods to precisely control a coolant pump in an internal combustion engine. The goal of this research is to minimize power consumption while still meeting optimal performance, reliability and durability requirements for an engine at all engine-operating conditions. This investigation achieves reduced fuel consumption, reduced emissions, and improved powertrain performance. Secondary impacts include cleaner air for the earth, reduced operating costs for the owner, and compliance with US regulatory requirements. The study utilizes mathematical modeling of the cooling system using heat transfer, pump laws, and boiling analysis to set limits to the cooling system and predict performance changes.

Abstract Powertrain simulations and catalyst studies showed the efficiency credits and feasibility of onboard reforming as a way to recover waste heat from heavy duty vehicles (HDVs) fueled by natural gas (NG). Onboard reforming involves 1) injecting NG into the exhaust gas recycle (EGR) loop of the HDV, 2) reforming NG on a catalyst in the EGR loop to hydrogen and carbon monoxide, and 3) combusting the reformed fuel in the engine. The reformed fuel has increased heating value (4-10% higher LHV) and flame speed over NG, allowing stable flames in spark ignition (SI) engines at EGR levels up to 25-30%. A sulfur-tolerant reforming catalyst was shown to reform a significant amount of NG (15-30% conversion) using amounts of precious metal near the current practice for HDV emissions control (10 g rhodium). Engine simulations showed that the high EGR levels enabled by onboard reforming are used most effectively to control engine load instead of waste-gating or throttling.

Abstract The study of road loads on trucks plays a major role in assessing the effect of heavy-vehicle design on fuel conservation measures. Coastdown testing with full-scale vehicles in the field offers a good avenue to extract drag components, provided that random instrumentation faults and biased environmental conditions do not introduce errors into the results. However, full-scale coastdown testing is expensive, and environmental biases which are ever-present are difficult to control in the results reduction. Procedures introduced to overcome the shortcomings of full-scale field testing, such as wind tunnels and computational fluid dynamics (CFD), though very reliable, mainly focus on estimating the effects of aerodynamic drag forces to the neglect of other road loads which should be considered.

Abstract This article analyses the flow field between two 1/8-scale Generalized European Transport System (GETS) models which are placed in a two-vehicle platoon at close distances. Numerical simulations using the lattice Boltzmann method together with a wind tunnel experiment (open jet facility, OJF) were executed. Next, to balance measurements, coaxial volumetric velocimetry (CVV) measurements were performed to obtain information about the flow field. Three intervehicle distances, 0.10, 0.45 and 0.91 times the vehicle length, were tested for various platoon configurations where the vehicles in the platoon varied in terms of front-edge radius and the addition of tails. At the smallest intervehicle distance, the greatest reductions in drag were found for both the leading and trailing vehicles. The flow in the gap between the two vehicles follows an S-shaped path with small variations between the configurations.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

Abstract The suspension system has been shown to have significant effects on vehicle performance, including handling, ride, component durability, and even energy efficiency during the design process. In this study, a new roll-plane hydraulically interconnected suspension (HIS) system is proposed to enhance both roll and lateral dynamics of a two-axle bus. The roll-plane stability analysis for the HIS system has been intensively explored in a number of studies, while only few efforts have been made for suspension tuning, especially considering lateral plane stability. This article aims to explore the integrated lateral and roll dynamics by suspension tuning of a two-axle bus equipped with HIS system. A ten-degree-of-freedom (DOF) lumped-mass vehicle model is integrated with either transient mechanical-hydraulic model for HIS or the traditional suspension components, namely, shock absorber and anti-roll bar (ARB).

A heavy truck wind tunnel test program is currently underway at the Langley Full Scale Tunnel (LFST). Seven passive drag reducing device configurations have been evaluated on a heavy truck model with the objective of understanding the practical limits to drag reduction achievable on a modern tractor trailer through add-on devices. The configurations tested include side skirts of varying length, a full gap seal, and tapered rear panels. All configurations were evaluated over a nominal 15 degree yaw sweep to establish wind averaged drag coefficients over a broad speed range using SAE J1252. The tests were conducted by first quantifying the benefit of each individual treatment and finally looking at the combined benefit of an ideal fully treated vehicle. Results show a maximum achievable gain in wind averaged drag coefficient (65 mph) of about 31 percent for the modern conventional-cab tractor-trailer.

The objective of the project was to conduct controlled test-track studies of solutions for achieving higher fuel efficiency and lower greenhouse gas emissions in the trucking industry. Using vehicles from five Canadian fleets, technologies from 12 suppliers were chosen for testing, including aerodynamic devices and low rolling resistance tires. The participating fleets also decided to conduct tests for evaluating the impact on fuel consumption of vehicle speed, close-following between vehicles, and lifting trailer axles on unloaded B-trains. Other tests targeted comparisons between trans-container road-trains and van semi-trailers road-trains, between curtain-sided semi-trailers, trans-containers and van semi-trailers, and between tractors pulling logging semi-trailers loaded with tree-length wood and short wood. The impact of a heavy-duty bumper on fuel consumption and the influence of B5 biodiesel blend on fuel consumption were also assessed.

Due to the diversity of Heavy Duty Vehicles (HDV), the European CO2 and fuel consumption monitoring methodology for HDVs will be based on a combination of component testing and vehicle simulation. In this context, one of the key input parameters that need to be accurately defined for achieving a representative and accurate fuel consumption simulation is the vehicle's aerodynamic drag. A highly repeatable, accurate and sensitive measurement methodology was needed, in order to capture small differences in the aerodynamic characteristics of different vehicle bodies. A measurement methodology is proposed which is based on constant speed measurements on a test track, the use of torque measurement systems and wind speed measurement. In order to support the development and evaluation of the proposed approach, a series of experiments were conducted on 2 different trucks, a Daimler 40 ton truck with a semi-trailer and a DAF 18 ton rigid truck.

Selective Catalytic Reduction (SCR) catalysts have been demonstrated as an effective solution for controlling NOx emissions from diesel engines. There is a drive to reduce the overall packaging volume of the aftertreatment system for these applications. In addition, more active SCR catalysts will be needed as the applications become more challenging: e.g. lower temperatures and higher engine out NOx, for fuel consumption improvements. One approach to meet the challenges of reduced volume and/or higher NOx reduction is to increase the active site density of the SCR catalyst by coating higher amount of SCR catalyst on high porosity substrates (HPS). This approach could enable the reduction of the overall packaging volume while maintaining similar NOx conversion as compared to 2010/2013 systems, or improve the NOx reduction performance for equivalent volume and NH3 slip.

Several drive cycles have been developed to describe heavy-duty class 8 truck tractor operations. However, regional delivery operations, consisting of a mix of urban and over-the-road driving using highways to access several delivery/pick-up sites in dense urban areas, have not been well described. With funding from the U.S. Army National Automotive Center, the High-efficiency Truck Users Forum (HTUF) developed two drive cycles in an effort to better describe the full range of Class 8 truck tractor operations, which in total consumed about 30 billion gallons of diesel in the United States in 2010. This paper describes the rational for and the process to develop two regional delivery drive cycles: HTUF Regional Delivery #1 and HTUF Regional Delivery #2. These cycles were developed from more than eight months of cumulative data collected on six diesel Class 8 truck tractors operating across North America and representing several types of truck vocations.

This paper presents a novel methodology to develop and validate fuel consumption models of Refuse Collecting Vehicles (RCVs). The model development is based on the improvement of the classic approach. The validation methodology is based on recording vehicle drive cycles by the use of a low cost data acquisition system and post processing them by the use of GPS and map data. The corrected data are used to feed the mathematical energy models and the fuel consumption is estimated. In order to validate the proposed system, the fuel consumption estimated from these models is compared with real filling station refueling records. This comparison shows that these models are accurate to within 5%.

The emergence of tougher environmental legislations and ever increasing demand for increased ride comfort, fuel efficiency, and low emissions have triggered exploration and advances towards more efficient vehicle gearbox technologies. The growing complexity and spatial distribution of such a mechatronic gearbox demands precise timing and coordination of the embedded electronics, integrated sensors and actuators as well as excellent overall reliability. The increased gearbox distributed systems have seen an increased dependence on sensors for feedback control, predominantly relying on hardware redundancy for faults diagnosis. However, the conventional hardware redundancy has disadvantages due to increased costs, weight, volume, power requirements and failure rates. This paper presents a virtual position sensor-based Fault Detection, Isolation and Accommodation (FDIA), which generates an analytical redundancy for comparison against the actual sensor output.