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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.

A carburetted, spark ignited gasoline fuelled engine of a 5 kW rated power generator was converted to run on hydrogen. As opposed to large parts of current research, the engine conversion’s foremost goal was not to maximise efficiency and power output but rather to find a cost-effective and low-complexity conversion approach to introduce clean fuels to existing engines. To allow for the increased volumetric fuel flow, the riser of the original carburettor was enlarged. The hydrogen flow into the venturi was metered with the help of a pressure regulator from a widely available conversion kit. The effects of different hydrogen-fuel-feed pressures on engine performance, operational stability and emission levels were examined experimentally. It was found that the hydrogen-line pressure before startup has to be set precisely (±5 mbar) to allow for stable and emission free operation.

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 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 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.

Eliminating toxic exhaust emissions, amongst them particulate matter (PM), is one of the driving factors behind the increasing use of electrified vehicles. However, it is frequently overseen that PM arise not only from combustion, but from non-exhaust traffic related causes as well; in particular from the vehicle brakes, tires and the road surface. Furthermore, as electrified vehicles weigh more and typically exhibit higher torques at low speeds, their non-exhaust emissions tend to be higher than for comparable conventional vehicles, especially those generated by tires. Fortunately, tire related emissions are directly related to tire wear, so that limiting tire wear can reduce these emissions as well. This can be accomplished by intelligently modulating the vehicle torque profile in real time, to limit the operation in conditions of higher tire wear.

The road freight transport sector is one of the main responsible for the air pollution (as the case of particulate matter) and greenhouse gases emissions worldwide. Different types of fuel technologies have been developed in order to improve efficiency, reduce air pollution impacts, such as the case of liquefied natural gas (LNG) for heavy-duty vehicles. Many studies show the relationship between the effects of short and long-term exposure to particulate matter (PM) and, according to the World Health Organization (WHO), premature deaths worldwide as well as cardiorespiratory diseases in elderly population are related to this pollutant. In this context, this paper aims at evaluating the atmospheric dispersion of PM in a stretch of a highway (Anhanguera-Bandeirantes) in the São Paulo State in Brazil due to the road freight transport considering the use of diesel and LNG in heavy-duty vehicles and the impacts on human health. The software AERMOD designed by U.S.

Nowadays, proton exchange membrane (PEM) fuel cell is widely seen as a promising energy conversion device especially for transportation application scenario because of its high efficiency, low operation temperature and nearly-zero road emission. Extensive modeling work have been done based on different dimensions during the past decades, including one-dimensional (1D), two-dimensional (2D), three-dimensional (3D) and intermediate combinations in between (e.g. “1+1D”). 1D model benefits from a rationally-chosen set of assumptions to obtain excellent calculation efficiency, yet at the cost of accuracy to some extent. In contrast, 3D model has great advantage over 1D model on acquiring more comprehensive information inside the fuel cell. For macro-scale modeling work, one compromise aiming to realize both acceptable computation speed and reasonable reflection of cell operation state is to simplify the membrane electrode assembly (MEA).

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.

Following market demands for a niche balance between engine performance and legislation requirement, a new-concept compressor scroll has been designed for small to medium size passenger cars. The design adopts a slight deviation from the conventional method, thus resulting in broader surge margin and better efficiency at off-design region. This paper presents the performance evaluation of the new compressor scroll on the cold-flow gas-stand followed by the on-engine testing. The testing program focused on back-to-back comparison with the standard compressor scroll, as well as identifying on-engine operational regime with better brake specific fuel consumption (BSFC) and transient performance. A specially instrumented 1.6L gasoline engine was used for this study. The engine control unit configuration is kept constant in both the compressor testing.

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.

Future CO2 emission legislation requires the internal combustion engine to become more efficient than ever. Of great importance is the boosting system enabling down-sizing and down-speeding. However, the thermodynamic coupling of a reciprocating internal combustion engine and a turbocharger poses a great challenge to the turbine as pulsating admission conditions are imposed onto the turbocharger turbine. This paper presents a novel approach to a turbocharger turbine development process and outlines this process using the example of an asymmetric twin scroll turbocharger applied to a heavy duty truck engine application. In a first step, relevant operating points are defined taking into account fuel consumption on reference routes for the target application. These operation points are transferred into transient boundary conditions imposed on the turbine.

Predicting Exterior Water Management is important for developing vehicles that meet customer expectations in adverse weather. Fluid film methods, with Lagrangian tracking, can provide spray and surface water simulations for complex vehicle geometries in on-road conditions. To cope with this complexity and provide practical engineering simulations, such methods rely on empirical sub-models to predict phenomena such as the film stripping from the surface. Experimental data to develop and validate such models is difficult to obtain therefore here a high-fidelity Coupled Level-set Volume of Fluid (CLSVOF) simulation is carried out. CLSVOF resolves the interface of the liquid in three dimensions; allowing direct simulation of film behaviour and interaction with the surrounding air. This is used to simulate a simplified wing-mirror, with air flow, on which water is introduced.

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.

The present work investigates the effect of fuel injection timing on combustion stratification and soot formation in an optically accessible, single cylinder light duty diesel engine. The engine operated under low load and low engine speed conditions, employing a single injection scheme. The conducted experiments considered three different injection timings, which promoted Partially Premixed Combustion (PPC) operation. The fuel quantity of the main injection was adjusted to maintain the same Indicated Mean Effective Pressure (IMEP) value among all cases considered. Findings were analysed via means of pressure trace and apparent heat transfer rate (AHTR) analyses, as well as a series of optical diagnostics techniques, namely flame natural luminosity, CH* and C2* chemiluminescence high-speed imaging, as well as planar Laser Induced Incandescence (pLII).

For the investigation of the tribological behavior of lubricated contacts, the choice and the calibration of the adopted asperity contact model is fundamental, in order to properly mimic the mixed lubrication conditions. The Greenwood/Tripp model is extensively adopted by the commercial software commonly employed to simulate lubricated contacts. This model, based on a statistic evaluation of the number of asperities in contact and on the Hertzian contact theory, has the advantage of introducing a simple relationship between oil film thickness and asperity contact pressure, considerably reducing the simulation time. However, in order to calibrate the model, some non-standard roughness parameters are required, that are not available from commercial roughness measuring equipment. Standard values, based on some limited experiences, are typically used, and a limited literature can be found focusing on how to evaluate them, thus reducing the predictivity of the model.

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.

The use of twin-scroll turbocharger turbine in automotive powertrain has been known for providing better transient performance over conventional single-scroll turbine. This has been accredited to the preservation of exhaust flow energy in the twin-scroll volute. In the current study, the performance comparison between a single and twin-scroll turbine has been made experimentally on a 1.5L passenger car gasoline engine. The uniqueness of the current study is that nearly identical engine hardware has been used for both the single and twin-scroll turbine volutes. This includes the intake and exhaust manifold geometry, turbocharger compressor, turbine rotor and volute scroll A/R variation trend over circumferential location. On top of that, the steady-state engine performance with both the volutes, has also been tuned to have matching brake torque.