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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.

A higher level of atomization of the fuel leads to a more homogeneous mixture with the air in internal combustion engines, whether they are equipped with direct injection or port fuel injected systems. The further break-up of the atomized fuel drops by the interaction of two fuel sprays is described in this paper. In the present research, a simulation of the collision and swirl of two fuel sprays in a double-injector engine concept is carried out through a qualitative comparison with the images obtained from the recorded video of the sprays and the results of the simulation. Previous work simulated and tested the spray interaction of fuel injectors on the top of the combustion chamber; while this research proposes a new approach to reduce the diameter of the atomized fuel drops through the direct collision of the sprays with injectors located oppositely and fully horizontally to get advantage of the flow’s momentum.

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.

A promising approach for defossilization in the transport sector is using the polymer electrolyte membrane fuel cell (PEMFC) as an energy converter for propulsion in combination with green hydrogen. Furthermore, hybridization can bring an additional gain in efficiency. In a hybrid electric vehicle (HEV) powertrain, including FCHEV, at least two power sources (e.g., an FC system (FCS) with a hydrogen storage system and a high-voltage battery (HVB)) provide the required propulsion power. Thus, the powertrain topology and the energy management strategy (EMS) of an FCHEV are more complex than those of a conventional powertrain. To ensure a cost- and time-efficient development process, the FCHEV powertrain concept and its functions must be verified and evaluated early. To this end, this study presents the design and setup of an FC-in-the-Loop (FCiL) test platform as a tool for the systematic development of an FCHEV powertrain under realistic operating conditions.

Synthetic fuels derived from renewable power sources, so-called e-fuels, will play a crucial role in achieving climate-neutral future mobility because they can be used in the existing fleets and in hard-to-decarbonize applications. In particular e-fuels that contain oxygen in their chemical structure can also burn more cleanly in terms of soot formation. For compression-ignition engines, polyoxymethylene dimethyl ethers (PODEs or OMEs) are among the most promising candidates for such oxygenated e-fuels. Here, we investigated the characteristics of injection and combustion of OME3-5 mixture compared to n-dodecane, a reference diesel-like fuel. Both single and multi-injection, comprising a short pilot injection, is used. Experiments were performed in a single-cylinder optically accessible Bowditch-type engine, injecting with 1500 bar pressure with a 3-hole injector (Spray B of the Engine Combustion Network).

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.

Cavitation is the major cause of the effective flow area reduction in fuel nozzles, together with mechanical damage, which leads to an increase of pressure losses. This paper describes the effect of different geometries along the fuel nozzle holes simulated with OpenFOAM® to control the cavitation and shape of the fuel jet. Previous work has only focused on the development trend towards conical spray holes that tapers towards the outlet with a strong rounded inlet edge, to increase the static pressure and thus reduce the cavitation tendency in nozzles; however, the jet forms a very narrow cone angle. The aim of this study is to evaluate the effect of constricted, expanded and gradually wider nozzles holes. The simulation reveals that the cavitation level can be changed and controlled depending on the geometry of the nozzle holes, the wider the inlet, the less is the cavitation; at the same time, the narrower the outlet, the better is the fuel atomization.

The continuous encouragement of lightweight design in modern vehicles demands a reliable and efficient method to predict and ameliorate the interior acoustic comfort for passengers. Due to considerable psychological effects on stress and concentration, the low frequency contribution plays a vital rule regarding interior noise perception. Apart other contributors, low frequency noise can be induced by transient aerodynamic excitation and the related structural vibrations. Assessing this disturbance requires the reliable simulation of the complex multi-physical mechanisms involved, such as transient aerodynamics, structural dynamics and acoustics. The domain of structural dynamics is particularly sensitive regarding the modelling of attachments restraining the vibrational behaviour of incorporated membrane-like structures. In a later development stage, when prototypes are available, it is therefore desirable to replace or update purely numerical models with experimental data.

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.

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.

We study in detail the flow mechanism, the aeroacoustic sources and its sound propagation in turbochargers by applying numerical simulations based on an appropriate aeroacoustic formulation. Thereby, we consider Lightill’s analogy for the investigation of the different noise mechanisms. The flow inside a turbocharger is highly turbulent and compressible. Thus, all three terms of Lighthill’s tensor are examined: (1) the Reynolds stress term, (2) the excess term and (3) the viscosity term. The investigations will be performed both in time and frequency domain, and we do a detailed study of the influences of different spatial and temporal discretizations.

Further development of exhaust aftertreatment systems based on selective catalytic reduction (SCR) requires detailed knowledge of all involved physical and chemical processes. One major influence is the impingement of the injected urea water solution (UWS) droplets on the hot walls of the exhaust system. Due to the numerous influencing factors of this complex phenomenon, it is described by empirical impingement maps based on experimental investigations. Frequently, the impacting droplet is assigned to a single impingement regime (e.g. splash) according to surface temperature and a kinetic parameter (e.g. Bai-Gosman, Bai-ONERA, Kuhnke). A transitional range between regimes has been reported experimentally before, but was abandoned in most cases for model simplification reasons. Only rarely a smooth transition for a selected regime boundary was implemented.

The permanently tightening emission regulations for nitrogen oxides (NOx) pollutants force further development of mobile exhaust aftertreatment systems with selective catalytic reduction (SCR). Of particular interest is the long-term reliability of SCR-systems with regard to unfavorable operating conditions, such as high injection rates of urea water solution (UWS) or low exhaust gas temperatures. Both may lead to the formation of solid deposits which decrease system efficiency by increasing backpressure and impairing ammonia formation. In order to study the most relevant processes of deposit formation, an optical box with heat resistant glass was designed. Three UWS injectors with different spray characteristics were used to study their influence on the deposit formation under a wide range of stationary and transient operating conditions. Infrared thermography was applied to observe spray-induced wall cooling, both below and above the Leidenfrost point.

The flows in-cylinder have a profound effect on the mixture preparation and subsequent combustion in all engines. These flows are highly three-dimensional in nature and information from multiple planes is required to characterise the flow dynamics. The flow measurements reported here are from three orthogonal planes in an optical access engine that is based on the Jaguar Land Rover AJ200 Gasoline Direct Injection (GDI) engine. Particle Image Velocimetry (PIV) measurements have been taken every 5°CA from the start of induction to the end of compression. Data have been obtained from 300 cycles for separate experiments measuring flows in the tumble plane, the swirl plane and the cross-tumble plane. Vector comparison metrics are used to quantitatively compare ensemble averaged PIV flow fields to Computational Fluid Dynamics (CFD) simulations across each plane in terms of both the velocity magnitude and direction.