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Vehicle efficiency and range, along with the DC charging speed, are deemed as the most important criteria for an electric vehicle currently. The electric vehicle energy consumption is impacted by the change in temperature along with the driving style and average speed of a customer, all other factors being constant. Hence understanding the patterns and impact of different aspects of an EV range & charging speed is crucial in delivering an electric vehicle with robust efficiency across all weather conditions. In this paper we have analysed vehicle parameters of global Jaguar I-PACE customer data. We present and analyse the collated big data of around 50,000+ unique vehicles with a data aggregate of well over 482 million km. In moderate ambient conditions the analysis indicated a good correlation with 50th to 75th percentile drivers’ energy consumption to the EPA label figure.

Energy management of battery electric vehicle (BEV) is a very important and complex multi-system optimisation problem. The thermal energy management of a BEV plays a crucial role in consistent efficiency and performance of vehicle in all weather conditions. But in order to manage the thermal management, it requires a significant number of temperature sensors throughout the car including high voltage batteries, thus increasing the cost, complexity and weight of the car. Virtual sensors can replace physical sensors with a data-driven, physical relation-driven or machine learning-based prediction approach. This paper presents a framework for the development of a neural network virtual sensor using a thermal system hardware-in-the-loop test rig as the target system. The various neural network topologies, including RNN, LSTM, GRU, and CNN, are evaluated to determine the most effective approach.

The rotor and stator of electric motors consist of multiple materials, of which steel forms the majority of mass and volume. Steel in electric motors is commonly in the form of thin sheets (laminations), stacked along the axis of the rotor. The structural integrity of such a stack can be ensured using bolting, welding or bonding of the laminations. Predictive mechanical finite element simulations of these laminated stacks can become computationally intense because the steel sheets are thin, and the motor often contains hundreds of them. If the laminations are modelled individually, the size of the elements is very small compared to the overall dimensions and the interface between the laminations need to be modelled as well. In this paper, we present an alternate method of modelling this laminated stack as a single solid body using homogeneous and orthotropic material property, instead of representing each lamination.

The modern luxurious electric vehicle (EV) demands high torque and high-speed requirements with increased range. Fulfilling these requirements gives rise to the need for increased efficiency and power density of the motors in the Electric Drive Unit (EDU). Internal Permanent Magnet (IPM) motor is one of the best suited options in such scenarios because of its primary advantages of higher efficiency and precise control over torque and speed. In the IPM motor, permanent magnets are mounted within the rotor body to produce a resultant rotating magnetic field with the 3-phase AC current supply in the stator. IPM configuration provides structural integrity and high dynamic performance as the magnets are inserted within the rotor body. Adhesive glue is used to install the magnets within the laminated stack of rotor.

Research and development studies regarding the internal combustion engines are, now more than ever, crucial in order to prevent a premature disposal for this application. An innovative technology is analyzed in this paper. The traditional slider-crank mechanism is replaced by a system of two ring-like elements crafted in such a way to transform the rotating motion of one element in the reciprocating motion of the other. This leads both to a less complex engine architecture and to the possibility to obtain a wide range of piston laws by changing the profile of the two cams. The relative motion of the cams is the peculiar feature of this engine and, due to this, alongside with the thermodynamic analysis, also the tribological aspects are investigated. 3D-CFD simulations are performed for several piston laws at different engine speeds to evaluate the cylinder pressure trace to be used as input data for the development of the tribological model.

This paper presents an experimental method for measuring transmission paths from the exterior to the interior of a passenger vehicle using a reciprocal approach: A production vehicle was placed in a semi-anechoic environment; artificial noise sources were placed at the location of the occupant’s ear(s) inside the vehicle and beamforming arrays with a total of more than 300 microphones were used to observe apparent noise sources on the vehicle exterior resulting from transmission paths. This makes it possible to quickly measure transmission paths over the whole vehicle body. One of the motivations for this work is the monitoring of sealing quality on production vehicles. Artificial seal breaches were introduced on the vehicle and a number of excitation signals were assessed to develop a method to detect and localise leakage noise sources.

The reduction in wind noise is increasingly important to vehicle designers as overall vehicle refinement increases. Customers often fit accessories such as roof bars to vehicles, with the aerodynamic interaction of these components generating aeroacoustic noise sources. These are often tonal in nature and of particular annoyance to occupants. Sensors for automated driving fitted to future vehicles may also have a similar detrimental effect on vehicle refinement. Therefore, careful design of such components is important to minimise dissatisfaction. This paper presents the combined application of acoustic beamforming in a full-scale aeroacoustic wind tunnel and the use of a Lattice Boltzmann Method CFD code to characterise the aeroacoustic performance of a roof bar design when fitted to a production vehicle.

For electric vehicles (EVs), driving range is one of the major concerns for wider customer acceptance and the cabin climate system represents the most significant auxiliary load for battery consumption. Unlike internally combustion engine (ICE) vehicles, EVs cannot utilize the waste heat from an engine to heat the cabin through the heating, ventilation and air conditioning (HVAC) system. Instead, EVs use battery energy for cabin heating, this reduces the driving range. To mitigate this situation, one of the most promising solutions is to optimize the recirculation of cabin air, to minimize the energy consumed by heating the cold ambient air through the HVAC system, whilst maintaining the same level of cabin comfort. However, the development of this controller is challenging, due to the coupled, nonlinear and multi-input multi-output nature of the HVAC and thermal systems.

The continued electrification of aircraft is required such that ambitious decarbonisation targets can be met. A significant challenge presented with this trend is the increased reliance on electrical systems to perform flight-critical operations in a manner that has not been seen in previous generations of aircraft. The power electronic converter is a key enabling technology in aircraft electrification. Its prevalence is such that the failure rate of flight critical-loads is closely linked with that of the associated power electronic converters. As such, there is a clear need to better understand the impact of improvements in both the reliability and failure estimation of novel power electronic converters at a systems level in future aerospace applications. Accordingly, this paper presents key highlights from literature on power converter research, summarising advances in reliability-enhancing features and more accurate Physics-of-Failure modelling methods.

Biofuels are a promising alternative to fossil fuels as their availability has been reduced during the last decades and they are the main sources of greenhouse gases emissions. Moreover, the targets of the international regulations include reduction of fossil fuels consumption, and improvement of the sustainability of the vehicle fleet. Blending gasoline with biofuels will result in changes in fuel blending procedures and combustion process especially for the gasoline direct injection (GDI) engines. In this article, flame visualization using chemiluminescence techniques in a Single Cylinder Optical Research Engine (SCORE) is presented, with an adjusted intake pressure of 850 mbar and early intake single injection (280 CAD BTDC), by using 100% hydrocarbon-based gasoline, E10 (90% gasoline - 10% ethanol) and ETBE20 (80% gasoline - 20% ethyl tert-butyl ether). ETBE20 is a potential alternative for E10, as it contains the same amount of renewable fuel and has low water solubility.

Hybrid technologies enable the reduction of noxious tailpipe emissions and conformance with ever-decreasing allowable homologation limits. The complexity of the hybrid powertrain technology leads to an energy management problem with multiple energy sinks and sources comprising the system resulting in a high-dimensional time dependent problem for which many solutions have been proposed. Methods that rely on accurate predictions of potential vehicle operations are demonstrably more optimal when compared to rule-based methodology [1]. In this paper, a previously proposed energy management strategy based on an offline optimization using dynamic programming is investigated. This is then coupled with an online model predictive control strategy to follow the predetermined optimal battery state of charge trajectory prescribed by the dynamic program.

The Range Rover Evoque is a compact luxury SUV, first introduced by Land Rover in 2012. Almost 800,000 units of the first-generation vehicle were sold. This paper explores some of the challenges entailed in developing the next generation of this successful product, maintaining key design cues while at the same time improving its aerodynamic efficiency. A development approach is outlined that made use of both numerical simulation and full-scale moving ground wind tunnel testing. A drag coefficient of 0.32 was obtained for the best derivative by paying particular attention to: the integration of active grille shutters; the front bumper and tyre package; brake cooling; underfloor design; wake control strategy; and detail optimization. This approach delivered the most aerodynamic Range Rover at the time of its introduction. The impact of these design changes on the aerodynamic flow field and consequently drag is highlighted.

In the frame of circular economy, wastes are perceived as sources not only for the recovery of high added-value compounds but also for energy production. Coffee is one of the most popular beverages with the consumption continuously increasing and generating huge amounts of solid residues in return. This solid waste after the extraction of the coffee beverage is known as Waste or Spent Coffee Grounds (WCG). Among others, the valorization has the potential to be directed as a bioresource for sustainable energy and particularly for the production of alternative liquid fuels for internal combustion engines. The aim of the current study is to formulate alternative fuel from WCG and to examine the fundamental properties per relevant specifications and requirements. Parameters related to stability, cold flow properties, lubricating characteristics and ignition quality are studied in comparison with other types of biodiesel fuel.

Government regulations and consumer needs are driving automotive manufacturers to reduce vehicle energy consumption. However, this forms part of a complex landscape of regulation and customer needs. For instance, when reducing aerodynamic drag or vehicle weight for efficiency other important factors must be taken into account. This is seen in vehicle bonnet design. The bonnet is a large unsupported structure that is exposed to very high and often fluctuating aerodynamic loads, due to travelling in the wake of other vehicles. When travelling at high speed and in close proximity to other vehicles this unsteady aerodynamic loading can force the bonnet structure to vibrate, so-called “bonnet flutter”. A bonnet which is stiff enough to not flutter may be either too heavy for efficiency or insufficiently compliant to meet pedestrian safety requirements. On the other hand, a bonnet which flutters may be structurally compromised or undermine customer perceptions of vehicle quality.

Accurate modelling for spray vapour fields is critical to enable adequate predictions of spray ignition and combustion characteristics of non-premixed reacting diesel sprays. Spray vapour characteristics are in turn controlled by liquid atomization and the KH-RT liquid jet break-up model is regularly used to predict this: with the KH model used for predicting primary break-up given its definition as a surface wave growth model, and the RT model used for predicting secondary break-up due to it being a drag based, stripping model. This paper investigates how the alteration of the switching position of the KH and RT sub-models within the KH-RT model impacts the resulting vapour field and ignition characteristics. The combustion prediction is handled by the implementation of a 54 species, 269 reaction skeletal mechanism utilising a Well Stirred Reactor model within the Star-CD CFD code.

In an era of rapidly increasing vehicle electrification, the gasoline engine remains a vital part of the passenger car powertrain portfolio. Lean-burn combustion is a formidable means for reducing the CO2 emissions of gasoline engines but demands the use of sophisticated emissions control. A 2.0 litre turbocharged direct-injection gasoline engine has been developed with a lean homogeneous combustion system matched to a robust lean and stoichiometric-capable exhaust aftertreatment. The aftertreatment system includes an SCR system and a GPF with filtration down to 10 nm particle size. The engine is equipped with a continuously variable valve-lift system, high-tumble ports and a high-energy ignition system; the boosting system comprises a variable geometry turbocharger and a 48 V electrical supercharger. The work reported formed part of the PaREGEn (Particle Reduced, Efficient Gasoline Engines) project under the Horizon 2020 framework programme.

Neural networks (NN) for marine engines, using raw measurement data from laboratory measurements, are developed and verified. These models can be utilized as virtual sensors of engine-out NOx emissions and lambda (λ). Investigations for the optimal NN configuration targeting models were carried so they can capture the dynamic behavior of a marine diesel engine, can generalize within the training range, and have the minimum complexity due to execution performance and portability reasons. Two configurations of NNs are investigated, the recurrent (RNN) and the time-delay neural network (TDNN). The resulting NN models are deployed on a prototype engine control unit (ECU) platform and are validated in real time for operating points and patterns that are not included in the training dataset. The real-time validation shows that the predicted quantities remain consistent in most operating areas and the dynamic behavior of the system is captured and reproduced accurately.

Contemporary trends are leading towards the electrification of aircraft for urban mobility applications. Accordingly, there is a high demand for advancements in light-weight, high voltage technologies to realize these new aircraft types. Driven by recent developments in the automotive industry, hybrid Pyrofuse protection devices have emerged as one such new candidate technology. Pyrofuses offer rapid clearance of fault currents, reduced cost and weight when compared to conventional mechanical breakers. In addition, Pyrofuses have the ability to tune the time-current curve to fit the application’s fault response characteristics. However, Pyrofuses are non-resettable devices whose exclusive use for electrical protection could present potential operational hazards and certification challenges in aerospace applications. Model-based analysis will be critical in supporting this evaluation.

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.

Many incidents associated with filter plugging have extensively been reported in microbially contaminated diesel and biodiesel fuel systems, especially under long term storage conditions. In this study a quantitative assessment of the undesirable insoluble solids produced in contaminated biodiesel fuels was carried out in order to evaluate their evolution rate during biodeterioration. For this purpose, a series of contaminated biodiesel fuel microcosms were prepared and stored for six months under stable conditions. The quantity of the particulate contaminants was monitored during storage by a multiple filtration technique which was followed at the end by a comparison with the active bioburden per ATP bioluminescence protocol. Additionally, identical microcosms were treated with a commercially available biocide in order to examine the latter’s activity both on solids formation and the microbial proliferation.