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With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

The growing demand for transportation fuels and the global emphasis on reducing greenhouse gas (GHG) emissions have led to increased interest in analyzing transport GHG emissions from the life-cycle perspective. Methanol, a potentially carbon-neutral fuel synthesized from CO2 and H2, has emerged as a promising candidate. This paper conducts a comprehensive life-cycle analysis (LCA) of the GHG emissions associated with the methanol production process, utilizing data inventory from China in 2019. To simulate the synthesis and distillation process of methanol, Aspen Plus is employed, using parameters obtained from actual plants. GHG emissions are then calculated using the GREET model, incorporating updated industry statistics and research findings. The CO2 necessary for methanol production is captured from factory flue gas.

Ethanol fuel blends with gasoline for spark ignition (SI) internal combustion engines are widely used on account of their advantages in terms of fuel economy and emissions reduction potential. The focus of this paper is to study the effects of these blends on combustion characteristics such as in-cylinder pressure profiles, gas-phase emissions (e.g., unburned hydrocarbons, NOx) and particulates (e.g., particulate matter and particle number) using both measurement campaigns and digital engineering workflows. Nineteen load-speed operating points in a 1L 3-cylinder GDI SI engine were measured and modelled. The measurements for in-cylinder pressure and emissions were repeated at each operating point for three types of fuel: gasoline (E0, 0% by volume of ethanol blend), E10 (10 % by volume of ethanol blend) and E20 (20% by volume of ethanol blend).

A heavy-duty diesel engine (ETH-LAV single cylinder MTU396 heavy duty research engine) was simulated by RANS and advanced reacting flow models to gain insight into its soot and NOx emissions. Due to symmetry, a section of the engine containing a single injector-hole was simulated. Dodecane was used as a surrogate to emulate the evaporation properties of diesel and a 22-step reaction mechanism for n-heptane was used to describe combustion. The Conditional Moment Closure (CMC) method was used as the combustion model in two ways. In a more conventional modelling approach, CMC was fully interfaced with the CFD and a two-equation model was employed for determining soot while the extended Zeldovich mechanism was used for NOx. In a second approach called the Imperfectly Stirred Reactor (ISR) method, the CMC equation was integrated over space and the previous RANS-CMC solution was further analysed in a post-processing step with the focus on soot.

Gasoline Direct Injection (GDI) vehicles now make up the majority of European new car sales and a significant share of the existing car parc. Despite delivering measurable engine efficiency benefits, GDI fuel systems are not without issues. Fuel injectors are susceptible to the formation of deposits in and around the injector nozzles holes. It is widely reported that these deposits can affect engine performance and that different fuels can alleviate the buildup of those deposits. This project aims to understand the underlying mechanisms of how deposit formation ultimately leads to a reduction in vehicle performance. Ten GDI fuel injectors, with differing levels of coking were taken from engine testing and consumer vehicles and compared using a range of imaging and engine tests. At the time of writing, a new GDI engine test is being developed by the Co-ordinating European Council (CEC) to be used by the fuel and fuel additive industry.

The Composite Lightweight Automotive Suspension System is a composite rear suspension knuckle/tieblade consisting of UD prepreg (epoxy resin), SMC (vinylester resin) carbon fibre and a steel insert to reduce the weight of the component by 35% and reduce Co2. The compression moulding manufacturing process and CAE optimisation are unique and ground-breaking for this product and are designed to allow high volume manufacture of approx. 30,000 vehicles per year. The manufacturing techniques employed allow for multi-material construction within a five minute cycle time to make the process viable for volume manufacture. The complexities of the design lie in the areas of manufacturing, CAE prediction and highly specialised design methods. It is a well-known fact that the performance of a composite part is primarily determined by the way it is manufactured.

This paper investigates the energy efficiency and emissions benefits possible with connected and autonomous vehicles (CAVs). Such benefits could be instrumental in decarbonising the transport sector. The impact of CAV technology on operation, usage and specification of vehicles for optimised energy efficiency is considered. Energy consumption reductions of 55% – 66% are identified for a fully autonomous road transport system versus the present. 46% is possible for a CAV on today’s roads. Smoothing effects and reduced stoppage in the drive cycle achieve a 31% reduction in travel time if speed limits are not reduced. CAV powertrain optimised for different scenarios requires just 10 kW – 40 kW maximum power whilst the vehicle mass is reduced by up to 40% relative to current cars. Urban-optimised powertrain, with only 10 kW – 15 kW maximum power, allows energy consumption reductions of over 71%.

The underbody of a truck is responsible for an appreciable portion of the vehicle’s aerodynamic drag, and thus its fuel consumption. This paper investigates experimentally the flow around side-skirts, a common underbody aerodynamic device which is known to be effective at reducing vehicle drag. A full, 1/10 scale European truck model is used. The chassis of the model is designed to represent one that would be found on a typical trailer, and is fully reconfigurable. Testing is carried out in a water towing tank, which allows the correct establishment of the ground flow and rotating wheels. Optical access into the underbody is possible through the clear working section of the facility. Stereoscopic and planar Particle Image Velocimetry (PIV) set-ups are used to provide both qualitative images of and quantitative information on the flow field.

Ambient temperature has significant impact on engine start ability and cold start emissions from diesel engines. These cold start emissions are accounted for substantial amount of the overall regulatory driving cycle emissions like NEDC or FTP. It is likely to implement the low temperature emissions tests for diesel vehicles, which is currently applicable only for gasoline vehicles. This paper investigates the potential of the intake heating strategy on reducing the driving cycle emissions from the latest generation of turbocharged common rail direct injection diesel engines at low ambient temperature conditions. For this investigation an air heater was installed upstream of the intake manifold and New European Driving Cycle (NEDC) tests were conducted at -7°C ambient temperature conditions for the different intake air temperatures. Intake air heating reduced the cranking time and improved the fuel economy at low ambient temperatures.

Diesel engines are the versatile power source and is widely used in passenger car and commercial vehicle applications. Environmental temperature conditions, fuel quality, fuel injection strategies and lubricant have influence on cold start performance of the diesel engines. Strategies to overcome the cold start problem at very low ambient temperature include preheating of intake air, coolant, cylinder block. The present research work investigates the effect of coolant temperatures on passenger car diesel engine’s performance and exhaust emission characteristics during the cold start at cold ambient temperature conditions. The engine is soaked in the -7°C environment for 6 hours. The engine coolant is preheated to the desired coolant temperatures of 10 and 20°C by an external heater and the start ability tests were performed.

In recent years magnetic resonance imaging (MRI) has been shown to be an attractive method for fluid flow visualization. In this work, we show how MRI velocimetry techniques can be used to non-invasively investigate and visualize the hydrodynamics of exhaust gas in a diesel particulate filter (DPF), both when clean and after loading with diesel engine exhaust particulate matter. The measurements have been used to directly measure the gas flow in the inlet and outlet channels of the DPF, both axial profiles along the length and profiles across the channel diameter. Further, from this information we show that it is possible to indirectly ascertain the superficial wall-flow gas velocity and the soot loading profiles along the filter channel length.

The higher cylinder peak pressure and pressure rise rate of modern diesel and gasoline fueled engines tend to increase combustion noise while customers demand lower noise. The multiple degrees of freedom in engine control and calibration mean there is more scope to influence combustion noise but this must first be measured before it can be balanced with other attributes. An efficient means to realize this is to calculate combustion noise from the in-cylinder pressure measurements that are routinely acquired as part of the engine development process. This publication reviews the techniques required to ensure accurate and precise combustion noise measurements. First, the dynamic range must be maximized by using an analogue to digital converter with sufficient number of bits and selecting an appropriate range in the test equipment.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

The performance of an organic Rankine cycle (ORC) that recovers heat from the exhaust of a heavy-duty diesel engine was simulated. The work was an extension of a prior study that simulated the performance of an experimental ORC system developed and tested at Oak Ridge National laboratory (ORNL). The experimental data were used to set model parameters and validate the results of that simulation. For the current study the model was adapted to consider a 15 liter turbocharged engine versus the original 1.9 liter light-duty automotive turbodiesel studied by ORNL. Exhaust flow rate and temperature data for the heavy-duty engine were obtained from Southwest Research Institute (SwRI) for a range of steady-state engine speeds and loads without EGR. Because of the considerably higher exhaust gas flow rates of the heavy-duty engine, relative to the engine tested by ORNL, a different heat exchanger type was considered in order to keep exhaust pressure drop within practical bounds.

Motivated by a combination of increasing consumer demand for fuel efficient vehicles, more stringent greenhouse gas, and anticipated future Corporate Average Fuel Economy (CAFE) standards, automotive manufacturers are working to innovate in all areas of vehicle design to improve fuel efficiency. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, reducing vehicle weight by using lighter materials and/or higher strength materials has been identified as one of the strategies in future vehicle development. Weight reduction in vehicle components, subsystems and systems not only reduces the energy needed to overcome inertia forces but also triggers additional mass reduction elsewhere and enables mass reduction in full vehicle levels.

Transfer or response equations are important as they provide relationships between the responses of different surrogates under matched, or nearly identical loading conditions. In the present study, transfer equations for different body regions were developed via mathematical modeling. Specifically, validated finite element models of the age-dependent Ford human body models (FHBM) and the mid-sized male Hybrid III (HIII50) were used to generate a set of matched cases (i.e., 192 frontal sled impact cases involving different restraints, impact speeds, severities, and FHBM age). For each impact, two restraint systems were evaluated: a standard three-point belt with and without a single-stage inflator airbag. Regression analyses were subsequently performed on the resulting FHBM- and HIII50-based responses. This approach was used to develop transfer equations for seven body regions: the head, neck, chest, pelvis, femur, tibia, and foot.

Wide Distillation Fuel (WDF) refers to the fuels with a distillation range from Initial Boiling Point (IBP) of gasoline to Final Boiling Point (FBP) of diesel. Polyoxymethylene Dimethyl Ethers (PODEn) have high oxygen content and cetane number, are promising green additive to diesel fuel. In this paper, WDF was prepared by blending diesel and gasoline at ratio of 1:1, by volume; the mass distribution of oligomers in the PODE3-4 product was 88.9% of PODE3 and 8.46% of PODE4. Diesel fuel (Diesel), WDF (G50D50) and WDF (80%)-PODE3-4 (20%) (G40D40P20) were tested in a light-duty single-cylinder diesel engine, combustion characteristic, fuel consumption and exhaust emissions were measured. The results showed that: at idling condition, G40D40P20 has better combustion stability, higher heat release rate, higher thermal efficiency compared with G50D50.

A study and analysis of the relation of biodiesel chemical structures to the resulting soot characteristics and soot oxidative reactivity is presented. Soot samples generated from combustion of various methyl esters, alkanes, biodiesel and diesel fuels in laminar co-flow diffusion flames are analyzed to evaluate the impact of fuel-bound oxygen in fatty acid esters on soot oxidation behavior. Thermogravimetric analysis (TGA) of soot samples collected from diffusion flames show that chemical variations in biodiesel ester compounds have an impact on soot oxidative reactivity and soot characteristics in contrast to findings reported previously in the literature. Soot derived from methyl esters with shorter alkyl chains, such as methyl butyrate and methyl hexanoate, exhibit higher reactivity than those with longer carbon chain lengths, such as methyl oleate, which are more representative of biodiesel fuels.

This paper presents a statistical characterisation of the effects of variations in vehicle parameters on vehicle road load data using a quarter vehicle as a case study. A model of a quarter vehicle test rig constructed from a commercial SUV is created in a multi-body dynamics (MBD) simulation environment to reproduce the real-life behaviour of the SUV. The model is thereafter validated by correlating the response data collected from both the model and laboratory test rig to the same road input. In order to ensure that only the effects of the variation of the vehicle parameters are captured, a time domain drive signal for a kerb strike road event on the physical vehicle is generated from the proving ground data collected during durability testing of the vehicle.

This research proposes the use of Artificial Neural Networks (ANN) to predict the road input for road load data generation for variants of a vehicle as vehicle parameters are modified. This is important to the design engineers while the vehicle variant is still in the initial stages of development, hence no prototypes are available and accurate proving ground data acquisition is not possible. ANNs are, with adequate training, capable of representing the complex relationships between inputs and outputs. This research explores the implementation of the ANN to predict road input for vehicle variants using a quarter vehicle test rig. The training and testing data for this research are collected from a validated quarter vehicle model.