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With the development of internet technology and autonomous vehicles (AVs), the multimodal transportation and distribution model based on AVs will be a typical application paradigm in the smart city scenario. Before AVs carry out logistics distribution, it is necessary to plan a reasonable distribution path based on each customer point, and this is also known as Vehicle Routing Problem (VRP). Unlike traditional VRP, the urban logistics distribution process based on multimodal transportation mode will use a set of different types of AVs, mainly including autonomous ground vehicles and unmanned aerial vehicles (UAVs). It is worth pointing out that there is currently no research on combining the planning of AVs distribution paths with the trajectory planning of UAVs. To address this issue, this article establishes a bilevel programming model. The upper-level model aims to plan the optimal delivery plan for AVs, while the lower-level model aims to plan a driving trajectory for UAVs.

Ammonia (NH3) is emerging as a potential fuel for longer range decarbonised heavy transport, predominantly due to favourable characteristics as an effective hydrogen carrier. This is despite generally unfavourable combustion and toxicity attributes, restricting end use to applications where robust health and safety protocols can always be upheld. In the currently reported work, a spark ignited thermodynamic single cylinder research engine was upgraded to include gaseous ammonia and hydrogen port injection fueling, with the aim of understanding maximum viable ammonia substitution ratios across the speed-load operating map. The work was conducted under stoichiometric conditions with the spark timing re-optimised for maximum brake torque at all stable logged sites. The experiments included industry standard measurements of combustion, performance and engine-out emissions.

Porous wall permeability is one of the most critical factors for the estimation of backpressure, a key performance indicator in automotive particulate filters. Current experimental and analytical filter models could be calibrated to predict the permeability of a specific filter. However, they fail to provide a reliable estimation for the dependence of the permeability on key parameters such as wall porosity and pore size. This study presents a novel methodology for experimentally determining the permeability of filter walls. The results from four substrates with different porosities and pore sizes are compared with several popular permeability estimation methods (experimental and analytical), and their validity for this application is assessed. It is shown that none of the assessed methods predict all permeability trends for all substrates, for cold or hot flow, indicating that other wall properties besides porosity and pore size are important.

Remote Monitoring and Teleoperation (RMTO) of Autonomous Vehicles (AV) is advancing rapidly in the industry. Researchers and industrial partners explore the role RMTO plays in helping AV navigate complicated situations, among many others. At the heart of this lies the problem of potential pathways and attack vectors or threat surfaces by which a malicious attack can be carried out on an RMTO and an AV. The separation of cybersecurity considerations in RMTO is barely considered, as so far, most available research and activities are mainly focused on AV. The main focus of this paper is addressing RMTO cybersecurity utilising an adaptable security-by-design approach, although security-by-design is still in the infant state within automotive cybersecurity. An adaptable security-by-design approach for RMTO covers Security Engineering Life-cycle, Logical Security Layered Concept, and Security Architecture.

Micro-mobility vehicles such as electric scooters and bikes are increasingly used for urban transportation; their designs usually trade off performance and range. Addressing thermal and cooling issues in such vehicles could enhance performance, reliability, life, and range. Limited packaging space within the wheels precludes the use of complex cooling systems that would also increase the cost and complexity of these mass-produced wheel motors. The present study begins by evaluating the external aerodynamics of the scooter to characterise the airflow conditions near the rotating wheel; then, a steady-state conjugate heat transfer model of a commercially available wheel hub motor (500W) is created using commercial computational fluid dynamics (CFD) software, StarCCM+. The CAD model of the motor used for this analysis has an external rotor permanent magnet (PM) brushless DC topology.

Engine downsizing is one the most common methods of coping with strict emission regulations. However, it must be coupled with complementary systems so that the engine performance would meet the standards. That is why new efficient solutions can pave the way toward this goal. The electric forced-induction system (EFIS) is the emerging replacement for conventional forced-induction systems (FIS), namely, turbochargers and superchargers. The reason behind this replacement is the drawbacks associated with FIS, among them are turbo lag and inefficiency in exhaust gas energy recycling. Electrically split turbocharger (EST) is a form of EFIS which offers a great potential for engine downsizing. In this paper, a new approach to EST utilization for lowering the fuel consumption (FC) without compromising performance has been introduced, through which the augmented degree of freedom enabled by an EST is used to optimize the air-charge boosting.

As the need for automotive assurance continues to grow, it becomes necessary to develop approaches which can provide assurance cases in a systematic and efficient manner. In the case of cybersecurity, this problem is exacerbated by the increasing complexity of vehicular onboard systems, their inherent obscurity due to their heterogenous architecture, emergent behaviors, and the disparate motivations and resources of potential threat agents. Furthermore, the advancement of connected autonomous vehicles (CAV) may allow external attackers to leverage the naïve trust ECUs have for adjacent devices to compromise the safety and security of the vehicle. To that end, there is an increased interest in automatically producing threat models such as attack trees, which usually rely on intensive expert driven construction or rudimentary formally defined processes, to identify potential threats to a vehicle.

The emergence of additive manufacturing (AM) technology has enabled the internal cooling channel layout for high pressure aluminium die casting (HPADC) tools to be designed and modified without topological constraint. Optimisation studies of a full industrial HPADC mould for extending the tool service life has received limited attention due to the high geometrical complexity and the various physics with multi time- and length- scales in addition to the manufacturability limitations. In this work, a new computationally efficient algorithm that employs the adjoint optimisation method has been developed to optimise the coolant channels layout in a complete mould with various 3D printed inserts. The algorithms significantly reduced the computational time and resources by decoupling the fluid flow in the coolant channels from the tool and simulating them separately.

The increased severity and prevalence of insoluble deposits formed on fuel injectors in gasoline direct injection (GDI) engines precipitates negative environmental, economic and healthcare impacts. A necessary step in mitigating deposits is to unravel the molecular compositions of these complex layered materials. But very little molecular data has been acquired. Mass spectrometry shows promise but most techniques require the use of solvents, making them unsuited for analyzing insoluble deposits. Here, we apply the high mass-resolving power and in-situ analysis capabilities of 3D OrbitrapTM secondary ion mass spectrometry (3D OrbiSIMS) to characterize deposits formed on the external tip and internal needle from a GDI injector. This is the first application of the technique to study internal GDI deposits. Polycyclic aromatic hydrocarbons (PAHs) are present up to higher maximum masses in the external deposit.

Additive manufacturing (AM) provides significant geometric design freedom for the cooling of high pressure die casting (HPDC) tools. Designing cooling channels that can achieve a uniform temperature throughout the tool-cast interface during the moulding process can limit part warping and sink marks, internal part stresses, and increase tool life. However, the design of the embedded cooling channels requires high computational resources to model the heat transfer process for the cast, mould, and coolant from the moment aluminium is injected into the cavity until the injection for the next cycle. To enable the examination of the effect of various parameters, a simplified 3-D CFD conjugate heat transfer model is introduced by considering the experimental observations. The model decouples the cast part from the mould.

Engine research has increasingly focused on emission of sub 23 nm particulates in recent years. Likewise, current legislative efforts are being made for particulate number (PN) emission limits to include this previously omitted size range. In Europe, PN measurement equipment and procedures for regulatory purposes are defined by the particle measurement programme (PMP). Latest regulation drafts for sub 23 nm measurements specify counting efficiencies with a 65% cut-off size at 10 nm (d65) and a minimum of 90% above 15 nm (d90). Even though alternative instruments, such as differential mobility spectrometers (DMS), are widely used in laboratory environments, the interpretation of their sub 23 nm measurements has not yet been widely discussed. For this study, particulate emissions of a 1.0L gasoline direct injection (GDI) engine have been measured with a DMS system for low to medium speeds with two load steps.

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.

Over the last decade, there has been an impetus in the automobile industry to develop new diesel injector systems, driven by a desire to reduce fuel consumption and proscribed by the requirement to fulfil legislation emissions. The modern common-rail diesel injector system has been developed by the industry to fulfil these aspirations, designed with ever-higher tolerances and pressures, which have led to concomitant increases in fuel temperatures after compression with reports of fuel temperatures of ~150°C at 1500-2500 bar. This engineering solution in combination with the introduction of Ultra Low Sulphur diesel fuel (ULSD) has been found to be highly sensitive to deposit formation both external injector deposits (EDID) and internal (IDID). The deposits have caused concerns for customers with poor spray patterns misfiring injector malfunction and failure, producing increased fuel consumption and emissions.

The impact of internal diesel injector deposits (IDIDs) on engine performance, efficiency and emissions remains a major concern in the automotive industry. This has been compounded in recent years by fuel injection equipment developments and changes to diesel fuel towards ultra-low sulfur diesel (ULSD) and biodiesel as well as the introduction of new fuels such as hydrotreated vegetable oil (HVO). Prevention and mitigation of such deposit formation requires an understanding of the formation process, which demands a chemical explanation. The chemistry of these deposits therefore remains a key research interest to the industry using the latest analytical methodologies to inform and build further on previous investigations.

Through improving the 48V hybrid vehicle archetype, governmental emission targets could be more easily met without incurring the high costs associated with increasing levels of electrification. The braking energy recovery function of hybrid vehicles is recognised as an effective solution to reduce emissions and fuel consumption in the short to medium term. The aim of this study was to evaluate methods to maximise the braking energy recovery capability of the 48V hybrid electric vehicle over pre-selected drive cycles using appropriately sized electrified components. The strategy adopted was based upon optimising the battery chemistry type via specific power capability, so that overall brake power is equal to the maximum battery charging power in a typical medium-sized passenger car under typical driving. This will maximise the regenerative braking energy whilst providing a larger torque assistance for a lower battery capacity.

This study presents a one-dimensional model for the prediction of the pressure loss across a wall-flow gasoline particulate filter (GPF). The model is an extension of the earlier models of Bissett [1] and Konstandopoulos and Johnson [2] to the turbulent flow regime, which may occur at high flow rates and temperatures characteristic of gasoline engine exhaust. A strength of the proposed model is that only one parameter (wall permeability) needs to be calibrated. An experimental study of flow losses for cold and hot flow is presented, and a good agreement is demonstrated. Unlike zero-dimensional models, this model provides information about the flow along the channels and thus can be extended for studies of soot and ash accumulation, heat transfer and reaction kinetics.

Characterization of soot nanoparticle morphology can be used to develop understanding of nanoparticle interaction with engine lubricant oil and its additives. It can be used to help direct modelling of soot-induced thickening, and in a more general sense for combatting reductions in engine efficiency that occur with soot-laden oils. Traditional 2D transmission electron microscopy (TEM) characterization possesses several important shortcomings related to accuracy that have prompted development of an alternative 3D characterization technique utilizing electron tomography, known as 3D-TEM. This work details progress made towards facilitating semi-automated image acquisition and processing for location of structures of interest on the TEM grid. Samples were taken from a four cylinder 1.4 L gasoline turbocharged direct injection (GTDI) engine operated in typically extra-urban driving conditions for 20,284 km, with automatic cylinder deactivation enabled.

The porous medium approach is widely used to represent high-resistance devices, such as catalysts, filters or heat exchangers. Because of its computational efficiency, it is invaluable when flow losses need to be predicted on a system level. One drawback of using the porous medium approach is the loss of detailed information downstream of the device. Correct evaluation of the turbulence downstream affects the calculation of the related properties, e.g. heat and mass transfer. The novel approach proposed in the current study is based on a modified distribution of the resistance across the porous medium, which allows to account for the single jets developing in the small channels, showing an improved prediction of the turbulence at the exit of the device, while keeping the low computational demand of the porous medium approach. The benefits and limitations of the current approach are discussed and presented by comparing the results with different numerical approaches and experiments.

Formation of soot is a known phenomenon for diesel engines, however, only recently emerged for gasoline engines with the introduction of direct injection systems. Soot-in-oil samples from a three-cylinder turbocharged gasoline direct injection (GDI) engine have been analysed. The samples were collected from the oil sump after periods of use in predominantly urban driving conditions with start-stop mode activated. Thermogravimetric analysis (TGA) was performed to measure the soot content in the drained oils. Soot deposition rates were similar to previously reported rates for diesel engines, i.e. 1 wt% per 15,000 km, thus indicating a similar importance. Morphology was assessed by transmission electron microscopy (TEM). Images showed fractal agglomerates comprising multiple primary particles with characteristic core-shell nanostructure. Furthermore, large amorphous structures were observed. Primary particle sizes ranged from 12 to 55 nm, with a mean diameter of 30 nm and mode at 31 nm.