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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.

The Euro VI Step E emission standard for heavy-duty vehicles (HDVs) is the first step to introduce cold-start emissions analysis as part of the on-road In-Service Conformity (ISC) requirements. The intention is to reflect the engine cold-start requirements foreseen in the World Harmonized Transient Cycle (WHTC) type approval cycle. In addition, a limit is introduced for solid particle number (PN) to be measured with Portable Emissions Measurement Systems (PEMS). The new regulatory step continues using the Moving Averaging Window (MAW) data post-processing prescribed by the Euro VI regulation, with additions to consider the cold-start emissions. In order to have a full understanding of the vehicle emissions performance during their daily operation, this study presents emissions data analysis of 25 Euro VI A-C and 3 Euro VI D vehicles. The aim is to screen for potential remaining high emission events during the day-to-day operation.

Current recommendations for restraining child occupants are based on biomechanical testing and data from national and international field studies primarily conducted prior to 2011. We hypothesized that analysis to identify factors associated with pediatric injury in motor-vehicle crashes using a national database of more recent police-reported crashes in the United States involving children under age 13 where type of child restraint system (CRS) is recorded would support previous recommendations. Weighted data were extracted from the National Automotive Sampling System General Estimates System (NASS-GES) for crash years 2010 to 2015. Injury outcomes were grouped as CO (possible and no injury) or KAB (killed, incapacitating injury, non-incapacitating injury). Restraint was characterized as optimal, suboptimal, or unrestrained based on current best practice recommendations. Analysis used survey methods to identify factors associated with injury.

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.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Occupant stature and body shape may have significant effects on injury risks in motor vehicle crashes, but the current finite element (FE) human body models (HBMs) only represent occupants with a few sizes and shapes. Our recent studies have demonstrated that, by using a mesh morphing method, parametric FE HBMs can be rapidly developed for representing a diverse population. However, the biofidelity of those models across a wide range of human attributes has not been established. Therefore, the objectives of this study are 1) to evaluate the accuracy of HBMs considering subject-specific geometry information, and 2) to apply the parametric HBMs in a sensitivity analysis for identifying the specific parameters affecting body responses in side impact conditions. Four side-impact tests with two male post-mortem human subjects (PMHSs) were selected to evaluate the accuracy of the geometry and impact responses of the morphed HBMs.

Since the introduction of Euro IV legislation [1, 2], Selective Catalytic Reduction (SCR) technology using liquid urea injection is (one of) the primary methods for NOx reduction in many applications. Ammonia (NH3) is the reagent and key element for the SCR system and its control calibration to meet all operational requirements. TNO and Horiba are highly motivated to facilitate a correct interpretation and use of emissions measurement data. Different hypotheses were defined to investigate the impact of temperatures and flow rates on urea decomposition. These parameters are known to strongly affect the urea decomposition process, and thus, the formation of NH3. During a test campaign, different SCR catalyst feed gas conditions (mass flow, temperature, species and dosing quantities) were applied. Three Horiba FTIR gas analyzers were installed to simultaneously sample either all upstream or all downstream of the SCR brick. Both steady-state and dynamic responses were evaluated.

Law enforcement officers (LEO) make extensive use of vehicles to perform their jobs, often spending large portions of a shift behind the wheel. Few LEO vehicles are purpose-built; the vast majority are modified civilian vehicles. Data from the field indicate that LEO suffer from relatively high levels musculoskeletal injury that may be due in part to poor accommodation provided by their vehicles. LEO are also exposed to elevated crash injury risk, which may be exacerbated by a compromise in the performance of the occupant restraint systems due to body-borne equipment. A pilot study was conducted to demonstrate the application of three-dimensional anthropometric scanning and measurement technology to address critical concerns related to vehicle design. Detailed posture and belt fit data were gathered from five law enforcement officers as they sat in the patrol vehicles that they regularly used and in a mockup of a mid-sized vehicle.

A vehicle parking manoeuvre is characterized by low or zero speed, small turning radius and large yaw velocity of the steered wheels. To predict the forces and moments generated by a wheel under these conditions, the Pacejka Magic Formula model has been extended to incorporate the effect of spin (turn slip model) in the past years. The extensions have been further developed and incorporated in the MFTyre/MF-Swift 6.2 model. This paper describes the development of a method for the identification of the turn slip parameters. Based on the operating conditions of a typical parking manoeuvre, the dominant parameters of the turn slip model are firstly defined. At an indoor test facility, the response of a tyre under the identified operating conditions is measured. An algorithm is developed to identify the dominant turn slip parameters from the measured responses.

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.

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test.

Eight whole fresh-frozen cadavers (6 female, 2 male) that were elderly and/or female were laterally impacted using UMTRI's dual-sled side-impact test facility. Cadavers were not excluded on the basis of old age or bone diseases that affect tolerance. A thinly padded, multi-segment impactor was used that independently measured force histories applied to the shoulder, thorax, abdomen, greater trochanter, iliac wing, and femur of each PMHS. Impactor plates were adjusted vertically and laterally toward the subject so that contact with body regions occurred simultaneously and so that each segment contacted the same region on every subject. This configuration minimized the effects of body shape on load sharing between regions. Prior to all tests, cadavers were CT scanned to check for pre-existing skeletal injuries. Cadavers were excluded if they had pre-existing rib fractures or had undergone CPR.

In the above-referenced study, kinematic response data of various body regions were reported. The response data for the left shoulder was incorrect, as it was in fact the right wrist. In this corrigendum, the corrected kinematic response data for the left shoulder is presented. This encompasses the individual kinematic responses and corridors, the statistical analysis and the implications on the discussion and conclusion.

A laboratory study of posture and belt fit was conducted with 46 men and 51 women, 61% of whom were age 60 years or older and 32% age 70 years or older. In addition, 28% of the 97 participants were obese, defined as body mass index ≥ 30 kg/m2. A mockup of a passenger vehicle driver's station was created and five belt anchorage configurations were produced by moving the buckle, outboard-upper (D-ring), and outboard-lower anchorages. An investigator recorded the three-dimensional locations of landmarks on the belt and the participant's body using a coordinate measurement machine. The location of the belt with respect to the underlying skeletal structures was analyzed, along with the length of belt webbing. Using linear regression models, an increase in age from 20 to 80 years resulted in the lap belt positioned 18 mm further forward relative to the pelvis, 26 mm greater lap belt webbing length, and 19 mm greater shoulder belt length.