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Porous wall permeability is one of the most critical factors for the estimation of backpressure, a key performance indicator in automotive particulate filters. Current experimental and analytical filter models could be calibrated to predict the permeability of a specific filter. However, they fail to provide a reliable estimation for the dependence of the permeability on key parameters such as wall porosity and pore size. This study presents a novel methodology for experimentally determining the permeability of filter walls. The results from four substrates with different porosities and pore sizes are compared with several popular permeability estimation methods (experimental and analytical), and their validity for this application is assessed. It is shown that none of the assessed methods predict all permeability trends for all substrates, for cold or hot flow, indicating that other wall properties besides porosity and pore size are important.

Bushing elasticity is one of the most important compliance factors that significantly influence driving behavior. The deformations of the bushings change the wheel orientations under external forces. Another important factor of bushing compliance is to provide a comfortable driving experience by isolating the vibrations from road irregularities. However, the driving comfort and driving dynamics are often in conflict and need to be balanced in terms of bushing compliance design. Specifically, lateral force steer and brake force steer are closely related to safety and stability and comprises must be minimized. The sensitivity analysis helps engineers to understand the critical bushing for certain compliance attributes, but optimal balancing is complicated to understand. The combination of individual bushing stiffness must be carefully set to achieve an acceptable level of all the attributes.

The present work represents the continuation of the introductory study presented in part I [11] where the experimental plan, the measurement system and the tools developed for the testing of a modern Wankel engine were illustrated. In this paper the motored data coming from the subsequent stage of the testing are presented. The AIE 225CS Wankel rotary engine produced by Advanced Innovative Engineering UK, installed in the test cell of the University of Bath and equipped with pressure transducers selected for the particular application, has been preliminarily tested under motored conditions in order to validate the data acquisition software on the real application and the correct determination of the Top Dead Centre (TDC) location which is of foremost importance in the computation of parameters such as the indicated work and the combustion heat release when the engine is tested later under fired conditions.

We describe experiments and numerical modeling of snow surface contamination on two simplified automotive bluff bodies: The Ahmed body and a wedge. The purpose was twofold: 1) To obtain well defined experimental results of snow contamination on simple geometries; 2) To propose a numerical modeling approach for snow contamination. The experiments were performed in a climatic wind tunnel using a snow cannon at −15 °C and the results show that the snow accumulation depends on the aerodynamics of the studied bluff bodies. Snow accumulates on surfaces in proximity to the aerodynamic wakes of the bodies and characteristic snow patterns are obtained on side surfaces. The numerical modeling approach consisted of an aerodynamic setup coupled with Lagrangian particle tracking. Particles were determined to adhere or rebound depending on an adhesion model combined with a resuspension criterion.

Permanent magnet (PM) electrical machine has far-reaching impacts in aviation electrification due to the continuous development in high power density and high efficiency electrical drives. The primary barrier to acceptance of permanent magnet machines for safety-critical starter-generator systems is its low fault-tolerance capability and low reliability (for the conventional designs). This article investigates a modular triple three-phase PM starter-generator comprehensively, including the tradeoff of fault-tolerant topology, optimization design process, analysis of electromagnetic (highlight the post-fault analysis) and thermal behavior, respectively. The triple three-phase segmented topology proposed meet the fault-tolerant requirement along with complete electrical, magnetic, and thermal isolation. There would be cost penalty on the proposed topology, but it gets offset by the ease of manufacturing of coils and their insertion.

Evolving of aircraft design towards further electrification requires safe and fault-free operation of all the components. More electric aircraft are increasingly utilizing electro-mechanical actuators (EMA). EMAs are prone to jamming and subsequent failure due to large forces on the shaft. Large forces are generated due to the high reflected inertia of the electric machine rotor. To limit the force acting on the shaft, a torque limiting device is connected to the power train which can separate the rotating mass of the electric machine from the power train. In this paper, a concept of integration of torque limiter and the electric machine rotor is presented to reduce overall volume and mass. It is connected closely with the rotor, within the motor envelope. A commercially available torque limiter and an electric machine designed for actuator application are used to demonstrate the concept. While essential for safety, the torque limiter adds to the mass and size of the overall EMA.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation.

The aim of the presented research is to propose and benchmark two brake models, namely the novel dynamic ILVO (Ilmenau-Volvo) model and a neural-network based regression. These can estimate the evolution of the brake friction between pad and disc under different load conditions, which are typically experienced in vehicle applications. The research also aims improving the knowledge of the underlying mechanism related to the evolution of the BLFC (boundary layer friction coefficient), the reliability of virtual environment simulations to speed up the product development time and reducing the amount of vehicle test in later phases and finally improving brake control functions. With the support of extensive brake dynamometer testing, the proposed models are benchmarked against State-of-the-Art. Both approaches are parametrized to render the friction coefficient dynamics with respect to the same input parameters.

Audio CAE is an emerging area of interest for vehicle OEMs. Questions regarding early stages of the vehicle design, like choosing the possible positions for speakers, deciding the installation details that can influence the visual design, and integration of the low frequency speakers with the body & closures structure, are of interest. Therefore, at VCC, the development of the CAE methodology for audio applications has been undertaken. The key to all CAE applications is the loudspeaker model made available in the vibro-acoustic software used within the company. Such a model has been developed, implemented and verified in different frequency ranges and different applications. The applications can be divided into the low frequency ones (concerning the installation of woofers and subwoofers), and the middle/high frequency ones (concerning the installation of midrange and tweeter speakers). In the case of the woofer, it is the interaction with the body vibration that is of interest.

Increasing demand for simulation accuracy often leads to increased finite element model complexity, which in turn, results in higher computational costs. As a provision, component mode synthesis approaches are employed to approximate the system response by using dynamic substructuring and model reduction techniques in linear systems. However, the use of available model reduction techniques in nonlinear problems containing the contact type of nonlinearities remains an interesting topic. In this paper, the application of a component mode synthesis method in squeak and rattle nonlinear simulation has been investigated. Critical regions for squeak and rattle of the side door model of a passenger car were modelled by nonlinear contact definition in finite element simulation. Craig-Bampton model reduction method was employed to substructure the finite element model while keeping the nonlinear contacts in the model.

The use of Wankel rotary engines as a range extender has been recognised as an appealing method to enhance the performance of Hybrid Electric Vehicles (HEV). They are effective alternatives to conventional reciprocating piston engines due to their considerable merits such as lightness, compactness, and higher power-to-weight ratio. However, further improvements on Wankel engines in terms of fuel economy and emissions are still needed. The objective of this work is to investigate the engine modelling methodology that is particularly suitable for the theoretical studies on Wankel engine dynamics and new control development. In this paper, control-oriented models are developed for a 225CS Wankel rotary engine produced by Advanced Innovative Engineering (AIE) UK Ltd. Through a synthesis approach that involves State Space (SS) principles and the artificial Neural Networks (NN), the Wankel engine models are derived by leveraging both first-principle knowledge and engine test data.

Dynamical Energy Analysis (DEA) has recently been introduced as a mesh-based high frequency method modelling structure borne sound for complex built-up structures. Using DEA, the structure-borne sound of an assembled agricultural tractor was calculated and good agreement between measurement and DEA calculations has been shown. However, it is still difficult to model a solid structure as currently DEA is based on wave-transmission calculations through plates and plate-to-plate junctions. Additionally, it is often difficult to generate accurate FE meshes of assembled complex structures because of welds, bolts, and rubber brushes between components. In this paper, we propose a novel method to generate DEA elements based on measurement data in order to model solid parts of a complex structures. The method of Advanced Transfer Path Analysis (ATPA) is employed to extract energy-transmission characteristics of a structure.

Reducing emissions from light duty vehicles is critical to meet current and future air quality targets. With more focus on real world emissions from light-duty vehicles, the interactions between engine and exhaust gas aftertreatment are critical. For modern engines, most emissions are generated during the warm-up phase following a cold start. For Diesel engines this is exaggerated due to colder exhaust temperatures and larger aftertreatment systems. The De-NOx aftertreatment can be particularly problematic. Engine manufacturers are required to take measures to address these temperature issues which often result in higher fuel consumption (retarding combustion, increasing engine load or reducing the Diesel air-fuel ratio). In this paper we consider an inner-insulated turbocharger as an alternative, passive technology which aims to reduce the exhaust heat losses between the engine and the aftertreatment. Firstly, the concept and design of the inner-insulated turbocharger is presented.

The need for a more complete understanding of the flow behavior in aerodynamic wind tunnels has increased as they have become vital tools not only for vehicle development, but also for vehicle certification. One important aspect of the behavior is the empty test section flow, which in a conventional tunnel should be as uniform as possible. In order to assess the uniformity and ensure consistent behavior over time, accurate measurements need to be performed regularly. Furthermore, the uncertainties and errors of the measurements need to be minimized in order to resolve small non-uniformities. In this work, the quantification of the measurement uncertainties from the full measurement chain of the new flow uniformity measurement rig for the Volvo Cars aerodynamic wind tunnel is presented. The simulation based method used to account for flow interference of the probe mount is also discussed.

Approximately 25 % of a passenger vehicle’s aerodynamic drag comes directly or indirectly from its wheels, indicating that the rim geometry is highly relevant for increasing the vehicle’s overall energy efficiency. An extensive experimental study is presented where a parametric model of the rim design was developed, and statistical methods were employed to isolate the aerodynamic effects of certain geometric rim parameters. In addition to wind tunnel force measurements, this study employed the flowfield measurement techniques of wake surveys, wheelhouse pressure measurements, and base pressure measurements to investigate and explain the most important parameters’ effects on the flowfield. In addition, a numerical model of the vehicle with various rim geometries was developed and used to further elucidate the effects of certain geometric parameters on the flow field.

In aerodynamic development of ground vehicles, the use of Computational Fluid Dynamics (CFD) is crucial for improving the aerodynamic performance, stability and comfort of the vehicle. Simulation time and accuracy are two key factors of a well working CFD procedure. Using scale-resolving simulations, accurate predictions of the flow field and aerodynamic forces are possible, but often leads to long simulation time. For a given solver, one of the most significant aspects of the simulation time/cost is the temporal resolution. In this study, this aspect is investigated using the realistic vehicle model DrivAer with the notchback geometry as the test case. To ensure a direct and accurate comparison with wind tunnel measurements, performed at TU Berlin, a large section of the wind tunnel is included in the simulation domain. All simulations are performed at a Reynolds number of 3.12 million, based on the vehicle length.

Wankel rotary engines are becoming an increasingly popular area of research with regard to their use as a range extender in the next generation of Hybrid Electric Vehicle (HEV). Due to their simple design, lightness, compactness and very favourable power-to-weight ratio, they represent one of the best alternative solutions to classic reciprocating piston engines. On the other hand, current Wankel engines still need improvements in terms of specific fuel consumption and emissions. This paper describes an innovative approach for the assessment of the performance of a modern rotary engine. All the experimental activities will be carried out within the Innovate UK funded ADAPT Intelligent Powertrain project led by Westfield Sportscars Limited.

Vector based control strategies have been extensively employed for drive systems, and in recent times to the More Electric Aircraft (MEA) generator based systems. The control schemes should maintain the bus voltage and adhere to the generator system voltage and current limits throughout a wide speed range. Typically, the current limit is prioritised first due to ease of implementation and simple control structure. As a result, the voltage limit can be exceeded due to change in operating conditions or disturbance factors. In flux weakening regions, this may affect the controllability of the power converter and lead to generator system instability. In this paper, an alternative control strategy has been investigated to address this drawback. The proposed control scheme refers to the modulation index limit which is the ratio between the power converter input and output voltages as the voltage limit.

Demonstrating the cost/benefits of technologies in the automotive sector is becoming very challenging because the benefits from technologies are sometimes of similar magnitude to testing precision. This paper aims to understand vehicle-borne imprecision and the effect of this on the quality of chassis dynamometer (CD) testing. Fuel consumption and NOx emissions precision is analyzed for two diesel vehicles with particulate filter and SCR systems. The two vehicles were tested on a high precision CD facility over the NEDC (New European Drive Cycle) and WLTC (World harmonized Light-duty Test Cycle) cycles. The CD base precision of testing was characterized between 0.6-3% depending on the cycle phase. A novel application of multi-variate statistical analysis was used to identify the factors that affected testing precision, allowing isolation of small differences that were not obvious when conducting cycle-averaged or cycle-phase-averaged analysis.