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The power demand of air conditioning in PHEVs is known to have a significant impact on the vehicle’s fuel economy and performance. Besides the cooling power associated to the passenger cabin, in many PHEVs, the air conditioning system provides power to cool the high voltage battery. Calculating the cooling power demands of the cabin and battery and their impact on the vehicle performance can help with developing optimum system design and energy management strategies. In this paper, a representative vehicle model is used to calculate these cooling requirements over a 24-hour duty cycle. A number of pre-cooling and after-run cooling strategies are studied and effect of each strategy on the performance of the vehicle including, energy efficiency, battery degradation and passenger thermal comfort are calculated. Results show that after-run cooling of the battery should be considered as it can lead to significant reductions in battery degradation.

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 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.

The ability to assess noise transmitted through seals to cabin interiors early in the design process is very important for automotive manufacturers. When a seal design is inadequate, the noise transmitted can dominate the interior noise, making the wind noise performance of the vehicle unacceptable. This can cause launch delays, increasing costs and risking loss of sales. Designing seals using conventional experimental processes is challenging, since the location and strength of flow noise sources are not known when the seal design is planned. Making changes to the seal system after the tooling stage is expensive for manufacturers as tooling and redesign costs can be considerable. Deliberate overdesign by adding multiple layers of seals in a wide range of locations also can reduce profit by unnecessarily raising part and manufacturing costs.

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 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.

A novel semi-analytical solution has been developed for the calculation of the static and dynamic response of an off road tire interacting with a deformable terrain, which utilizes soil parameters independent of the size of the contact patch (size-independent). The models involved in the solution presented, can be categorized in rigid and/or pneumatic tires, with or without tread pattern. After a concise literature review of related methods, a detailed presentation of the semi-analytical solution is presented, along with assumptions and limitations. A flowchart is provided, showing the main steps of the numerical implementation, and various test cases have been examined, characterized in terms of vertical load, tire dimensions, soil properties, deformability of the tire, and tread pattern. It has been found that the proposed model can qualitatively capture the response of a rolling wheel on deformable terrain.

Vibration Isolation is the key objective of engine mounting systems in the automotive industry. A well-designed, robust engine mount must be capable of isolating the engine assembly from road-based excitations. Owing to high vibration inputs, engine mounts are susceptible to wear and failure. Thus, the durability of engine mounts is a cause for concern. A design validation methodology has been developed at Jaguar Land Rover using Multibody Dynamics (MBD) to enhance the prognosis of engine mount loads during full - vehicle durability test events. This paper describes the development of a virtual multi-axial simulation table rig (MAST Rig) to test virtual engine mount designs. For the particular example considered in this paper, a simple sinusoidal input is applied to the MAST Rig. The development of the virtual MAST Rig has been described including details of the modelling methodology.

Sports Utility Vehicles (SUVs) typically have a blunt rear end shape (for design and practicality), however this is not beneficial for aerodynamic drag. Drag can be reduced by a number of passive and active methods such as tapering and blowing into the base. In an effort to combine these effects and to reduce the drag of a visually square geometry slots have been introduced in the upper side and roof trailing edges of a squareback geometry, to take air from the freestream and passively injects it into the base of the vehicle to effectively create a tapered body. This investigation has been conducted in the Loughborough University’s Large Wind Tunnel with the ¼ scale generic SUV model. The basic aerodynamic effect of a range of body tapers and straight slots have been assessed for 0° yaw. This includes force and pressure measurements for most configurations.

Vehicle rear and side body soiling has been a concern since the earliest cars. Traditionally, soiling has been seen to be less importance than vehicle aerodynamics and acoustics. However, increased reliance on sensors and cameras to assist the driver means that there are more surfaces of the vehicle that must be kept clean. Failure to take this into consideration means risking low customer satisfaction with new features. This is because they are likely to fail under normal operating conditions and require constant cleaning. This paper numerically investigates features known to have an influence on side and rear face soiling with a demonstration vehicle. These changes include rim design, diffuser strakes and diffuser sharpening. While an exhaustive investigation of these features is beyond the scope of this study, examples of each feature will be considered.

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.

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.