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By building on mature internal combustion engine (ICE) hardware combined with dedicated hydrogen (H2) technology, the H2-ICE has excellent potential to accelerate CO2 reduction. H2-ICE concepts can therefore contribute to realizing the climate targets in an acceptable timeframe. In the landscape of H2-ICE combustion concepts, High Pressure Direct Injection (HPDI™) is an attractive option considering its high thermal efficiency, wide load range and its applicability to on-road as well as off-road heavy-duty equipment. Still, H2-HPDI is characterized by diffusion combustion, giving rise to significant NOx emissions. In this paper, the potential of H2-HPDI toward compliance with future emissions legislation is explored on a 1.8L single-cylinder research engine. With tests on multiple load-speed points, Exhaust Gas Recirculation (EGR) was shown to be an effective measure for reducing engine-out NOx, although at the cost of a few efficiency points.

Lean-burn hydrogen internal combustion engines are a good option for future transportation solutions since they do not emit carbon-dioxide and unburned hydro-carbons, and the emissions of nitric-oxides (NOx) can be kept low. However, under lean-burn conditions the combustion duration increases, and the combustion stability decreases, leading to a reduced thermal efficiency. Turbulent jet ignition (TJI) can be used to extend the lean-burn limit, while decreasing the combustion duration and improving combustion stability. The objective of this paper is to investigate the feasibility of a passive pre-chamber TJI system on a heavy-duty hydrogen engine under lean-burn conditions using CFD modelling. The studied concept is mono-fuel, port-fuel injected, and spark ignited in the pre-chamber. The overall design of the pre-chamber is discussed and the effect of design parameters on the engine performance are studied.

The current European fleet of vehicles is ageing and lifetime mileages are rising proportionally. Consequently, a substantial fraction of the vehicle fleet is currently operating at mileages well beyond current durability legislation (≤ 160,000 km). Emissions inventories and models show substantial increases in emissions with increasing mileage, but knowledge of the effect of emissions control system deterioration at very high mileages is sparse. Emissions testing has been conducted on matched pairs (or more) of diesel and gasoline (and CNG) vehicles, of low and high mileage, supplementing the results with in-house data, in order to explore high mileage emission deterioration factors (DF). The study isolated, as far as possible, the effect of emissions deterioration with mileage, by using nominally identical vehicle models and controlling other variables.

Self-learning energy management is a promising concept, which optimizes real-world system performance by automated, on-line adaptation of control settings. In this work, the potential of self-learning capabilities related to optimization is studied for energy management in Plug-in Hybrid Electric Vehicles (PHEV). These vehicles are of great interest for the transport sector, since they combine high fuel efficiency with last mile full-electric driving. We focus on a specific use case: PHEV operation through future Zero Emission (ZE) zones of cities. As a first step towards self-learning control, we introduce a novel, adaptive supervisory controller that combines modular energy and emission management (MEEM) and deals with varying constraints and system uncertainty. This optimal control strategy is based on Pontryagin’s Minimum Principle and maximizes overall energy efficiency.

A model-based control approach is proposed to give proper reference for the feed-forward combustion control of Partially Pre-mixed Combustion (PPC) engines. The current study presents a simplified first principal model, which has been developed to provide a base estimation of the ignition properties. This model is used to describe the behavior of a single-cylinder heavy-duty diesel engine fueled with a mix of bio-butanol and n-heptane (80vol% bio-butanol and 20 vol% n-heptane). The model has been validated at 8 bar gross Indicated Mean Effective Pressure (gIMEP) in PPC mode. Inlet temperature and pressure have been varied to test the model capabilities. First the experiments were conducted to generate reference points with BH80 under PPC conditions. And then CFD simulations were conducted to give initial parameter set up, e.g. fuel distribution, zone dividing, for the multi-zone model.

At present, the hydrogen combustion engine has gained renewed interest from the heavy-duty internal combustion engine (ICE) industry as an enabler for fast decarbonization of well-to-wheel emissions and reinforced by the vast commitment of key stakeholders to establish a green hydrogen infrastructure. Past studies have often focused on partial substitution of the primary hydrocarbon fuel by hydrogen in spark ignition and compression ignition engines. Studied 100% hydrogen combustion engines are dominantly of the premixed spark ignition type using port fuel hydrogen injection. In this study, a wider look at other hydrogen ICE concepts has been taken that may bear high potential to overcome some of the limitations of using hydrogen for high power applications. The studied concepts vary from port injection to direct injection of hydrogen and from spark ignition to compression ignition.

Reactivity Controlled Compression Ignition (RCCI) combines very high thermal efficiencies with ultra-low engine out NOx and PM emissions. Moreover, it enables the use of a wide range of fuels. As this pre-mixed combustion concept relies on controlled auto-ignition, closed-loop combustion control is essential to guarantee safe and stable operation under varying operating conditions. This work presents a coordinated air-fuel path controller for RCCI operation in a multi-cylinder heavy-duty engine. This is an essential step towards real-world application. Up to now, transient RCCI studies focused on individual cylinder control of the fuel path only. A systematic, model-based approach is followed to design a multivariable RCCI controller. Using the Frequency Response Function (FRF) method, linear models are identified for the air path and for the combustion process in the individual cylinders.

The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers’ head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset.

Existing gasoline DI injection equipment has been modified to generate single hole pulsed gas jets. Injection experiments have been performed at combinations of 3 different pressure ratios (2 of which supercritical) respectively 3 different hole geometries (i.e. length to diameter ratios). Injection was into a pressure chamber with optical access. Injection pressures and injector hole geometry were selected to be representative of current and near-future DI natural gas engines. Each injector hole design has been characterized by measuring its discharge coefficient for different Re-levels. Transient jets produced by these injectors have been visualized using planar laser sheet Mie scattering (PLMS). For this the injected gas was seeded with small oil droplets. The corresponding flow field was measured using particle image velocimetry (PIV) laser diagnostics.

This study outlines a protocol for image data collection acquired from human volunteers. The data set will serve as the foundation of a consolidated effort to develop the next generation full-body Finite Element Analysis (FEA) models for injury prediction and prevention. The geometry of these models will be based off the anatomy of four individuals meeting extensive prescreening requirements and representing the 5th and 50th percentile female, and the 50th and 95th percentile male. Target values for anthropometry are determined by literature sources. Because of the relative strengths of various modalities commonly in use today in the clinical and engineering worlds, a multi-modality approach is outlined. This approach involves the use of Computed Tomography (CT), upright and closed-bore Magnetic Resonance Imaging (MRI), and external anthropometric measurements.

This paper reviews the field operational test (FOT) methodology adopted in recent years for the evaluation of driver-assistance systems. The Road Departure Crash Warning System program is used both for illustration and as a case study. This project involved an extensive field operational test of a driver-assistance system using volunteers from the general public who drove instrumented research vehicles in place of their normal cars. Objective and subjective data were collected in these trials, and comparisons were made between driving behavior under conditions where the systems were either enabled or disabled. This paper presents sample results from the analyses and draws conclusions on the strengths and weaknesses of the FOT method.

This paper (1) summarizes previous human factors/safety research on parking (8 studies, mostly over 20 years old), (2) provides statistics for 10,400 parking-related crashes in Michigan from 2000-2002, and (3) summarizes interviews with 6 insurance agents concerning parking crashes. These sources indicate: 1 About 1/2 to 3/4 of parking crashes involve backing, often into another moving vehicle while emerging from a parking stall. 2 Eight-and-a-half foot-wide stalls had higher crash rates than wider stalls. 3 Most parallel parking crashes occur on major streets, not minor streets. 4 Lighting and driver impairment were minor factors in parking crashes.

A method has been developed to identify and document the locations of rib fractures from two-dimensional CT images obtained from occupants of crashes investigated in the Crash Injury Research Engineering Network (CIREN). The location of each rib fracture includes the vertical location by rib number (1 through 12), the lateral location by side of the thorax (inboard and outboard), and the circumferential location by five 36-degree segments relative to the sternum and spine. The latter include anterior, anterior-lateral, lateral, posterior-lateral, and posterior regions. 3D reconstructed images of the whole ribcage created from the 2D CT images using Voxar software are used to help identify fractures and their rib number. A geometric method for consistently locating each fracture circumferentially is described.

This study was conducted to resolve discrepancies and fill in gaps in the biomechanical impact response of the human abdomen to frontal impact loading. Three types of abdominal loading were studied: rigid-bar impacts, seatbelt loading, and close-proximity (out-of-position) airbag deployments. Eleven rigid-bar free-back tests were performed into the mid and upper abdomens of unembalmed instrumented human cadavers using nominal impact speeds of 6 and 9 m/s. Seven fixed-back rigid-bar tests were also conducted at 3, 6, and 9 m/s using one cadaver to examine the effects of body mass, spinal flexion, and repeated testing. Load-penetration corridors were developed and compared to those previously established by other researchers. Six seatbelt tests were conducted using three cadavers and a peak-loading rate of 3 m/s. The seatbelt loading tests were designed to maximize belt/abdomen interaction and were not necessarily representative of real-world crashes.

This study continued the biomechanical investigations of forearm fractures caused by direct loading of steering-wheel airbags during the early stages of deployment. Twenty-four static deployments of driver airbags were conducted into the forearms of unembalmed whole cadavers using a range of airbags, including airbags that are depowered as allowed by the new federal requirements for frontal impact testing. In general, the depowered airbags showed a reduction in incidence and severity of forearm fractures compared to the pre-depowered airbags tested. Data from these twenty-four tests were combined with results from previous studies to develop a refined empirical model for fracture occurrence based on Average Distal Forearm Speed (ADFS), and a revised value for fifty-percent probability of forearm-bone fracture of 10.5 m/s. Bone mineral content, which is directly related to forearm tolerance, was found to be linearly related to arm mass.

Few studies have systematically examined the effects of truck and bus workstation geometry on driver posture and position. This paper presents methods for determining drivers' postural responses and preferred component locations using a reconfigurable vehicle mockup. Body landmark locations recorded using a three-dimensional digitizer are used to compute a skeletal-linkage representation of the drivers' posture. A sequential adjustment procedure is used to determine the preferred positions and orientations of key components, including the seat, steering wheel, and pedals. Data gathered using these methods will be used to create new design tools for trucks and buses, including models of driver-selected seat position, eye location, and needed component adjustment ranges. The results will also be used to create accurate posture-prediction models for use with human modeling software.

This paper describes control system and psychological concepts enabling the development of a simulation model suitable for use in emulating driver performance in situations involving the longitudinal control of the distance and headway-time to a preceding vehicle. The developed model has mathematical expressions and relationships pertaining to the driver's skill in operating the brake and accelerator (“inverse dynamics”) and the driver's perceptual and decision-making capabilities (“desired dynamics”). Simulation results for driving situations involving braking and accelerating are presented to aid in understanding the research work.

The tests described here have been used to provide a preliminary checkout of the control functionality of a prototype adaptive cruise control (ACC) system being used in a field operational test of intelligent cruise control. The results presented provide an initial characterization of the headway control performance of the ACC system. The inputs to these tests are the speed of the preceding vehicle. The results of the tests are based upon measurements of range, range rate, velocity, transmission shift commands, and velocity commands resident within the ACC system. Numerical performance measures are derived from these data and used to characterize system performance quantitatively. Results from these types of tests could be used in assessing differences in headway control characteristics associated with various ACC systems.

This paper describes an ongoing effort to develop computer-simulated instrumentation for the UMTRI Driver Interface Research Simulator. The speedometer, tachometer, engine and fuel gauges, along with warning lights are back projected onto a screen in front of the driver. The image is generated by a Macintosh running LabVIEW. Simulated instrumentation (instead of a production cluster) was provided so that new display designs can be rapidly generated and tested. This paper addresses the requirements for prototyping software, the advantages and disadvantages of the packages available, and the UMTRI implementation of the software, and its incorporation into the driving simulator.

This paper describes the architecture and use of a simulation graphical user interface (SGUI) that uses new (1990's) computer hardware and software concepts to provide an easy-to-use environment for simulating vehicle dynamics. The user interacts with windows, buttons, and pop-up menus, in a multitasking environment such as UNIX, Windows®, or Mac OS®. The SGUI reduces the level of computer expertise required of the user. Most information is shown in a graphic context, and “what if?” options are selected by clicking buttons and selecting from pop-up menus. The SGUI is organized as a data base of vehicles, vehicle parts, vehicle inputs, and simulation results. The organization makes it easy for users to assemble the component data needed to (1) simulate new systems, (2) run simulation programs automatically, and (3) view the results graphically. The SGUI is assembled from low-cost software components.