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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.

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.

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.

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.

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.

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.

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.

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.

Improved fuel economy is increasingly a key measure of performance in the automotive industry driven by market demands and tighter emissions regulations. Within this environment, one way to improve fuel economy is via fuel additives that deliver friction- reducing components to the piston-cylinder wall interface. Whilst the use of friction modifiers (FMs) in fuel or lubricant additives to achieve fuel economy improvements is not new, demonstrating the efficacy of these FMs in vehicles is challenging and requires statistical design together with carefully controlled test conditions. This paper describes a bespoke, efficient, high-precision vehicle testing procedure designed to evaluate the fuel economy credentials of fuel-borne FMs. By their nature, FMs persist on engine surfaces and so their effects are not immediately reversible upon changing to a non FM-containing fuel (“carryover” effect), therefore requiring careful design of the test programme.

Worldwide, Fuel Economy (FE) legislation increasingly influences vehicle and engine design, and drives friction reduction. The link between lubricant formulation and mechanical friction is complex and depends on engine component design and test cycle. This Motored Friction Tear Down (MFTD) study characterizes the friction within a 3.6L V6 engine under operating conditions and lubricant choices relevant to the legislated FE cycles. The high-fidelity MFTD results presented indicate that the engine is a low-friction engine tolerant of low viscosity oils. Experiments spanned four groups of engine hardware (reciprocating, crankshaft, valvetrain, oil pump), five lubricants (four candidates referenced against an SAE 0W-20) and five temperature regimes. The candidate lubricants explored the impact of base oil viscosity, viscosity modifier (VM) and friction modifier (FM) content.

The HyPACE (Hybrid Petrol Advanced Combustion Engine) project is a part UK government funded research project established to develop a high thermal efficiency petrol engine that is optimized for hybrid vehicle applications. The project combines the capabilities of a number of partners (Jaguar Land Rover, BorgWarner, MAHLE Powertrain, Johnson Matthey, Cambustion and Oxford University) with the target of achieving a 10% vehicle fuel consumption reduction, whilst still achieving a 90 to 100 kW/liter power rating through the novel application of a combination of new technologies. The baseline engine for the project was Jaguar Land Rover’s new Ingenium 4-cylinder petrol engine which includes an advanced continuously variable intake valve actuation mechanism. A concept study has been undertaken and detailed combustion Computational Fluid Dynamics (CFD) models have been developed to enable the optimization of the combustion system layout of the engine.

Under bonnet thermal encapsulation is a method for retaining the heat generated by a running powertrain after it is turned off. By retaining the heat in the engine bay, the powertrain will be closer to its operating temperatures the next time it is started, reducing the warm up time required. This reduces the period of inefficiency due to high friction losses before the engine reaches it operating temperature, and as a result reduces the vehicles fuel consumption and CO2 emissions. To develop an integrated and efficient encapsulation design, CAE methods can be applied to allow this work stream to start as early in a vehicles development cycle as possible. In this work, the existing test methods are discussed, and a new Thermal CFD method is presented that accurately simulates the fluid temperatures after a customer representative 9 hour park period.