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Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries.

DHT hybrid transmission assembly control system discussed in this paper includes hydraulic control, hybrid mode switching control, shift control, dual motor control, clutch and motor thermal management. The hybrid mode is divided into four modes: the EV mode, the serial mode, the parallel mode and the launch mode. Hydraulic control includes torque-pressure conversion, clutch pressure kiss point adaption, clutch oil filling time adaption. Shift control includes shift type decision, shift sequence control, shift inertia process based on motor intervention. Thermal management includes clutch flow and motor flow distribution. Motor control include the current control, mode control and boost strategy of permanent magnet synchronous motor in dual hybrid system, which has good stability and robustness. Motor mode includes initialization mode, normal mode, fault mode, active discharge mode, power off mode.

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.

Injector fouling is an important contributory factor to particulate matter (PM) emissions in Gasoline Direct Injection (GDI) engines. Several publications have emerged in recent years which acknowledge the benefits of injector cleanliness, but others claim that high levels of Deposit Control Additive (DCA) could have detrimental effects that outweigh the benefits of the augmented cleaning potential. The paper is divided into two parts: The first part contains a critical review of the literature linking injector cleanliness and particulate matter emissions, and studies assessing the impact of higher treat rates of additives. The second part of the paper describes new evidence of the beneficial effects of DCAs, in the form of several separate (previously unpublished) studies, using both engines and vehicles. In this newly reported work, various DCA treat rates were employed, and some of the fuels had measured UWG levels well in excess of 50 mg/100 mL.

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).

Lithium-ion batteries (LiBs) have been widely used in electrified vehicles, and the battery thermal management (BTM) system is needed to maintain the temperature that is critical to battery performance, safety, and health. Conventionally, three-dimensional battery thermal models are developed at the early stage to guide the design of the BTM system, in which battery thermophysical parameters (radial thermal conductivity, axial thermal conductivity, and specific heat capacity) are required. However, in most literature, those parameters were estimated with greatly different values (up to one order of magnitude). In this paper, an investigation is carried out to evaluate the magnitude of the influence of those parameters on the battery simulation results. The study will determine if accurate measurements of battery thermophysical parameters are necessary.

With increased awareness and scrutiny of greenhouse gas (GHG) emissions, the heavy-duty truck industry is on the lookout for solutions that can maximize GHG savings, through either lowering fuel consumption and lowering methane slip. This paper focuses on whether it is possible to provide a differentiated Liquefied Natural Gas (LNG) that supports the further improvement of a High-Pressure Direct Injection (HPDI) Engine. Desired improvements from this LNG blend are the lowering or substitution of the pilot Diesel use of the current HPDI engine, the lowering of the raw exhaust gas methane concentration and any additional performance improvements. Sixty-five substances were identified that could potentially be blended into cryogenic methane thus creating a differentiated LNG fuel.

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.

In Gasoline Direct Injection engines, direct exposure of the injector to the flame can cause combustion products to accumulate on the nozzle, which can result in increased particulate emissions. This research observes the impact of injector fouling on particulate emissions and the associated injector spray pattern and shows how both can be reversed by utilising fuel detergency. For this purpose multi-hole injectors were deliberately fouled in a four-cylinder test engine with two different base fuels. During a four hour injector fouling cycle particulate numbers (PN) increased by up to two orders of magnitude. The drift could be reversed by switching to a fuel blend that contained a detergent additive. In addition, it was possible to completely avoid any PN increase, when the detergent containing fuel was used from the beginning of the test. Microscopy showed that increased injector fouling coincided with increased particulate emissions.

The purpose of this work was to gain a fundamental understanding of which fuel property parameters are responsible for particulate emission characteristics, associated with key intermediate behavior in the engine cylinder such as the fuel film and insufficient mixing. Accordingly, engine tests were carried out using various fuels having different volatility and chemical compositions under different coolant temperature conditions. In addition, a fundamental spray and film visualization analysis was also conducted using a constant volume vessel, assuming the engine test conditions. As for the physical effects, the test results showed that a low volatility fuel displayed high particulate number (PN) emissions when the injection timing was advanced. The fundamental test clearly showed that the amount of fuel film on the impingement plate increased under such operating conditions with a low volatility fuel.

Certain diesel fuel specification properties are considered to be environmental parameters according to the European Fuels Quality Directive (FQD, 2009/EC/30) and previous regulations. These limits included in the EN 590 specification were derived from the European Programme on Emissions, Fuels and Engine Technologies (EPEFE) which was carried out in the 1990’s on diesel vehicles meeting Euro 2 emissions standards. These limits could potentially constrain FAME blending levels higher than 7% v/v. In addition, no significant work has been conducted since to investigate whether relaxing these limits would give rise to performance or emissions debits or fuel consumption benefits in more modern vehicles. The objective of this test programme was to evaluate the impact of specific diesel properties on emissions and fuel consumption in Euro 4, Euro 5 and Euro 6 light-duty diesel vehicle technologies.

Octane appetite of modern engines has changed as engine designs have evolved to meet performance, emissions, fuel economy and other demands. The octane appetite of seven modern vehicles was studied in accordance with the octane index equation OI=RON-KS, where K is an operating condition specific constant and S is the fuel sensitivity (RONMON). Engines with a displacement of 2.0L and below and different combinations of boosting, fuel injection, and compression ratios were tested using a decorrelated RONMON matrix of eight fuels. Power and acceleration performance were used to determine the K values for corresponding operating points. Previous studies have shown that vehicles manufactured up to 20 years ago mostly exhibited negative K values and the fuels with higher RON and higher sensitivity tended to perform better.

Most modern high-pressure common rail diesel fuel injection systems employ an internal pressure equalization system in order to support needle lift, enabling precise control of the injected fuel mass. This results in the return of a fraction of the high-pressure diesel back to the fuel tank. The diesel fuel flow occurring in the injector spill passages is expected to be a cavitating flow, which is known to promote fuel ageing. The cavitation of diesel promotes nano-particle formation through induced pyrolysis and oxidation, which may result in deposits in the vehicle fuel system. A purpose-built high-pressure cavitation flow rig has been employed to investigate the stability of unadditised crude-oil derived diesel and paraffin-blend model diesel, which were subjected to continuous hydrodynamic cavitation flow across a single-hole research diesel nozzle.

High-speed planar laser Mie scattering and Laser Induced Fluorescence (PLIF) were employed for the determination of Sauter Mean Diameter (SMD) distribution in non-evaporating diesel sprays. The effect of rail pressure, distillation profile, and consequent fuel viscosity on the drop size distribution developing during primary and secondary atomization was investigated. Samples of conventional crude-oil derived middle-distillate diesel and light distillate kerosene were delivered into an optically accessible mini-sac injector, using a customized high-pressure common rail diesel fuel injection system. Two optical channels were employed to capture images of elastic Mie and inelastic LIF scattering simultaneously on a high-speed video camera at 10 kHz. Results are presented for sprays obtained at maximum needle lift during the injection. These reveal that the emergent sprays exhibit axial asymmetry and vorticity.

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.

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.

There is increasing demand for engine diagnostic and control with in-cylinder pressure signal. However, the application of cylinder pressure sensors are restricted by the high cost of the sensor. Another possible way for engine combustion state estimation is by processing of instantaneous crankshaft speed signal, but it is limited by the precision and complexity of the algorithm. It could be a solution by processing one cylinder pressure signal in combination with a crankshaft speed signal. The indicated torque could be estimated through engine speed processing and also from the measure cylinder pressure for the reference cylinder. Measurement results from experiments show that the indicated torque error traces of different cylinder are similar in shape. According to this assumption, the reference cylinder with cylinder pressure signal available can serve as both a parameter calibration information source and an error reduction measure.

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.