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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.

Injector nozzle deposits can have a profound effect on particulate emissions from vehicles fitted with Gasoline Direct Injection (GDI) engines. Several recent publications acknowledge the benefits of using Deposit Control Additives (DCA) to maintain or restore injector cleanliness and in turn minimise particulates, but others claim that high levels of DCA could have detrimental effects due to the direct contribution of DCA to particulates, that outweigh the benefits of injector cleanliness. Much of the aforementioned work was conducted in laboratory scenarios with model fuels. In this investigation a fleet of 7 used GDI vehicles were taken from the field to determine the net impact of DCAs on particulates in real-world scenarios. The vehicles tested comprised a range of vehicles from different manufacturers that were certified to Euro 5 and Euro 6 emissions standards.

It is useful for research purposes to define simple surrogate gasoline compositions that can replicate the chemical and physical properties of more complex mixtures. Ethanol is used in commercially available gasolines around the world as part of the pathway to the decarbonization of the transportation sector. In this study equations were developed to predict the Research Octane Number (RON), Motor Octane Number (MON) and Dry Vapour Pressure Equivalent (DVPE) of gasoline surrogates containing ethanol (10-25 vol%), isopentane, n-heptane, isooctane and toluene. The non-linear blending behaviour associated with ethanol is found to necessitate coefficients in the equations developed for MON that are a function of ethanol content, whereas surprisingly the equations for RON and DVPE do not need this added level of complexity.

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.

Exhaust Gas Recirculation (EGR) is employed in diesel engines to reduce engine-out NOx emissions. Despite the concerted design efforts of manufacturers, high-pressure Exhaust Gas Recirculation (HP-EGR) systems can be susceptible to fouling as the particulate matter, hydrocarbons and other entrained species deposit from the exhaust gas flow as it cools on its passage through the EGR system. Such deposits can lead to a number of problems including deterioration of emissions, fuel efficiency, performance and drivability, as well as breakdowns. The development of an engine test method to enable the study of the impact of fuel on deposits in the HP-EGR system was reported in 2020. In the test, a 4-cylinder light-duty diesel engine of 1.6L displacement runs at conditions conducive to EGR deposit formation over 24 hours and the impact of fuels on deposit formation is determined through weighing of the EGR system components before and after the test.

Design efforts to improve the hydraulic efficiency of high-pressure diesel fuel systems and thus further improve overall engine efficiency have resulted in the utilisation of low-spill control valves and reduced injector component clearances to reduce general leakage losses. Overall, these advances have contributed significantly to the high efficiency diesel engines of today. However, the combination of very high fuel pressures, cavitation and low fuel leakage volumes increases the heating of the remaining fuel, increasing temperature and, in turn, the propensity for deposits to form inside the injector. This deposit phenomenon is commonly known as Internal Diesel Injector Deposits (IDID) and can cause rough engine running and failed engine starts requiring injector cleaning or replacement. Methods studying this phenomenon are under development in the industry.

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.

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 the present study, Large Eddy Simulations (LES) have been performed with a 3D model of a step nozzle injector, using n-pentane as the injected fluid, a representative of the high-volatility components in gasoline. The influence of fuel temperature and injection pressure were investigated in conditions that shed light on engine cold-start, a phenomenon prevalent in a number of combustion applications, albeit not extensively studied. The test cases provide an impression of the in-nozzle phase change and the near-nozzle spray structure across different cavitation regimes. Results for the 20oC fuel temperature case (supercavitating regime) depict the formation of a continuous cavitation region that extends to the nozzle outlet. Collapse-induced pressure wave dynamics near the outlet cause a transient entrainment of air from the discharge chamber towards the nozzle.

Exhaust Gas Recirculation (EGR) is employed in diesel engines to reduce engine-out NOx. Carbon-containing deposits form in the EGR systems of modern diesel engines as the particulate matter, hydrocarbons and other entrained species deposit from the exhaust gas flow as it cools. Much work has been done by Original Equipment Manufacturers (OEMs) to reduce deposits and mitigate their effects by optimized dimensioning of EGR coolers and valves, introduction of EGR cooler bypass for use in the most sensitive cold conditions and experimenting with oxidation catalysts upstream of the EGR system. Nevertheless, deposits forming in the high-pressure Exhaust Gas Recirculation (HP-EGR) systems of modern diesel engines can sometimes lead to a number of problems including emissions and fuel consumption deterioration, poor performance and drivability, as well as breakdowns. An engine test method has been developed to enable the impact of fuel on deposits in the HP-EGR system to be studied.

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.

Plug-in electric vehicle (PHEV) has a promising prospect to reduce greenhouse gas (GHG) emission and optimize engine operating in high-efficiency region. According to the maximum electric power and all-electric range, PHEVs are divided into two categories, including “all-electric PHEV” and “blended PHEV” and the latter provides a potential for more rational energy distribution because engine participates in vehicle driving during aggressive acceleration not just by motor. However, the frequent use of engine may result in severe emissions especially in low state of charge (SOC) and ahead of catalyst light-off. This study quantitatively investigates the impact of oil viscosity and driving mode (hybrid/conventional) on oil dilution and emissions including particle number (PN).

Full hybrid electric vehicles are usually defined by their capability to drive in a fully electric mode, offering the advantage that they do not produce any emissions at the point of use. This is particularly important in built up areas, where localized emissions in the form of NOx and particulate matter may worsen health issues such as respiratory disease. However, high degrees of electrification also mean that waste heat from the internal combustion engine is often not available for heating the cabin and for maintaining the temperature of the powertrain and emissions control system. If not managed properly, this can result in increased fuel consumption, exhaust emissions, and reduced electric-only range at moderately high or low ambient temperatures negating many of the benefits of the electrification. This paper describes the development of a holistic, modular vehicle model designed for development of an integrated thermal energy management strategy.

In use cars often drive through the wakes of other vehicles. It has long been appreciated that this imposes a fluctuating onset flow which can excite a structural response in vehicle panels, particularly the bonnet. This structure must be designed to be robust to such excitation to guarantee structural integrity and maintain customer expectations of quality. As we move towards autonomous vehicles and exploit platoons for drag reduction, this onset flow condition merits further attention. The work reported here comprises both measurements and simulation capturing the unsteady pressure distribution over the bonnet of an SUV following a similar vehicle at high speed and in relatively close proximity. Measurements were taken during track testing and include 48 static measurement locations distributed over the bonnet where the unsteady static pressures were recorded.

Fuel with higher octane content is playing a key role in optimising engine performance by allowing a more optimal spark timing which leads to increased engine efficiency and lower CO2 emissions. In a previous study the impact of octane was investigated with a fleet of 20 vehicles using market representative fuels, varying from RON 91 to 100. The resulting data showed a clear performance and acceleration benefit when higher RON fuel was used. In this follow-up study 10 more vehicles were added to the database. The vehicle fleet was extended to be more representative of Asian markets, thus broadening the geographical relevance of the database, as well as adding vehicles with newer technologies such as boosted down-sized direct injection engines, or higher compression ratio engines. Eight different fuel combinations varying in RON were tested, representing standard gasoline and premium gasoline in different markets around the world.

Downsized turbocharged gasoline direct injection (TGDI) engines with high specific power and torque can enable reduced fuel consumption in passenger vehicles while maintaining or even improving on the performance of larger naturally aspirated engines. However, high specific torque levels, especially at low speeds, can lead to abnormal combustion phenomena such as knock or Low-Speed Pre-Ignition (LSPI). LSPI, in particular, can limit further downsizing due to resulting and potentially damaging mega-knock events. Herein, we characterize the impacts of lubricant and fuel composition on LSPI frequency in a TGDI engine while specifically exploring the correlation between fuel composition, particulate emissions, and LSPI events. Our research shows that: (1) oil composition has a strong impact on LSPI frequency and that LSPI frequency can be reduced through a carefully focused approach to lubricant formulation.

The field of vision of the driver during wet road conditions is essential for safety at all times. Additionally, the safe use of the increasing number of sensors integrated in modern cars for autonomous driving and intelligent driver assistant systems has to be ensured even under challenging weather conditions. To fulfil these requirements during the development process of new cars, experimental and numerical investigations of vehicle soiling are performed. This paper presents the surface contamination of self- and foreign-soiling tested in the wind tunnel. For these type of tests, the fluorescence method is state-of-the-art and widely used for visualizing critical areas. In the last years, the importance of parameters like the contact angle have been identified when designing the experimental setup. In addition, new visualization techniques have been introduced.

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.