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Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

Designing a lightweight and durable engine is universally important from the standpoints of fuel economy, vehicle dynamics and cost. However, it is challenging to theoretically find an optimal solution which meets both requirements in products such as the cylinder head, to which various thermal loads and mechanical loads are simultaneously applied. In our research, we focused on “non-parametric optimization” and attempted to establish a new design approach derived from the weight reduction of a cylinder head. Our optimization process consists of topology optimization and shape optimization. In the topology optimization process, we explored an optimal structure with the theoretically-highest stiffness in the given design space. This is to provide an efficient structure for pursuing both lightweight and durable characteristics in the subsequent shape optimization process.

Vehicle development involves the design and integration of subsystems of different domains to meet performance, efficiency, and emissions targets set during the initial developmental stages. Before a physical prototype of a vehicle or vehicle powertrain is tested, engineers build and test virtual prototypes of the design(s) on multiple stages throughout the development cycle. In addition, controllers and physical prototypes of subsystems are tested under simulated signals before a physical prototype of the vehicle is available. Different departments within an automotive company tend to use different modelling and simulation tools specific to the needs of their specific engineering discipline. While this makes sense considering the development of the said system, subsystem, or component, modern holistic vehicle engineering requires the constituent parts to operate in synergy with one-another in order to ensure vehicle-level optimal performance.

It is essential to include uncertainties in the simulation process in order to perform reliable vibroacoustic predictions in the early design phase. In this contribution, uncertainties are quantified using the generalized Polynomial Chaos (gPC) expansion in combination with a Finite Element (FE) model of a vehicle body in white. It is the objective to particularly investigate the applicability of the gPC method in the industrial context with a high number of uncertain parameters and computationally expensive models. A non-intrusive gPC expansion of first and second order is implemented and the approximation of a stochastic response process is compared to a Latin Hypercube sampling based reference solution with special regard to accuracy and computational efficiency. Furthermore, the method is examined for other input distributions and transferred to another FE model in order to verify the applicability of the gPC method in practical applications.

During the last decades, big steps have been taken towards a realistic simulation of NVH (Noise Vibration Harshness) behavior of vehicles using the Finite Element (FE) method. The quality of these computation models has been substantially increased and the accessible frequency range has been widened. Nevertheless, to perform a reliable prediction of the vehicle vibroacoustic behavior, the consideration of uncertainties is crucial. With this approach there are many challenges on the way to valid and useful simulation models and they can be divided into three areas: the input uncertainties, the propagation of uncertainties through the FE model and finally the statistical output quantities. Each of them must be investigated to choose sufficient methods for a valid and fast prediction of vehicle body vibroacoustics. It can be shown by rough estimation that dimensionality of the corresponding random space for different types of uncertainty is tremendously high.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Structure-borne inputs to hybrid FEA/SEA models could have significant effects on the model prediction accuracy. The purpose of this work was to obtain the structure-borne noise (SBN) inputs using a simplified transfer path analysis (TPA) and identify the significance of the structure-borne and airborne contributions to the spectator sound power of an engine with enclosure for future modeling references. Force inputs to the enclosure from the engine were obtained and used as inputs to a hybrid engine enclosure model for sound prediction.

Surface contamination, or soiling, of the exterior of road vehicles can be unsightly, can reduce visibility and customer satisfaction, and, with the increasing application of surface-mounted sensors, can degrade the performance of advanced driver-assistance systems. Experimental methods of evaluating surface contamination are increasingly used in the product development process, but the results are generally subjective. The use of computational methods for predicting contamination makes objective measures possible, but comparable data from experiment is an important validation requirement. This article describes the development of an objective measure of surface contamination arising during experiments. A series of controlled experiments using ultraviolet (UV) dye-doped water are conducted to develop a robust methodology. This process is then applied to a simplified contamination test.

Vehicle surface contamination is an important design consideration as it affects drivers’ vision and the performance of onboard camera and sensor systems. Previous work has shown that eddy-resolving methods are able to accurately capture the flow field and particle transport, leading to good agreement for vehicle soiling with experiments. What is less clear is whether the secondary breakup, coalescence, and evaporation of liquid particles play an important role in spray dynamics. The work reported here attempts to answer this and also give an idea of the computational cost associated with these extra physics models. A quarter-scale generic Sports Utility Vehicle (SUV) model is used as a test case in which the continuous phase is solved using the Spalart-Allmaras Improved Delayed Detached Eddy Simulation (IDDES) model. The dispersed phase is computed concurrently with the continuous phase using the Lagrangian approach.

In a real-world environment, a vehicle on the road is subjected to a range of flow yaw angles, the most severe of which can impact handling and stability. A fully coupled, six degrees-of-freedom CFD and vehicle handling simulation has modelled the complete closed loop system. Varying flow yaw angles are introduced via time dependent boundary conditions and aerodynamic loads predicted, whilst a handling model running simultaneously calculates the resulting vehicle response. Updates to the vehicle position and orientation within the CFD simulation are achieved using the overset grid method. Using this approach, a crosswind simulation that follows the parameters of ISO 12021:2010 (Sensitivity to lateral wind - Open-loop test method using wind generator input), was performed using the fastback variant of the DrivAer model. Fully coupled aerodynamic and vehicle response was compared to that obtained using the simplified quasi-steady and unsteady, one way coupled method.

This paper demonstrates the use of large scale tomographic PIV to study the wake region of a Windsor model. This forms part of a larger study intending to understand the mechanisms that drive drag force changes when rear end optimizations are applied. For the first time, tomographic PIV has been applied to a large airflow volume (0.125m3, 500 x 500 x 500mm), which is of sufficient size to capture the near wake of a 25% scale Windsor model in a single measurement. The measurement volume is illuminated using a 200mJ double pulsed Nd:Yag laser fitted with a volume optic and seeded with 300μm helium filled soap bubbles generated by a novel high output seeder. Images were captured using four 4M Pixel LaVision cameras. The tomographic results are shown to produce high quality data with the setup used, but further improvements and tests at higher Reynolds number could be conducted if an additional seeding rake was used to increase seeding density.

Efficiency and durability are key areas of research and development in modern racing drivetrains. Stringent regulations necessitate the need for components capable of operating under highly loaded conditions whilst being efficient and reliable. Downsizing, increasing the power-to-weight ratio and modification of gear teeth geometry to reduce friction are some of the actions undertaken to achieve these objectives. These approaches can however result in reduced structural integrity and component durability. Achieving a balance between system reliability and optimal efficiency requires detailed integrated multidisciplinary analyses, with the consideration of system dynamics, contact mechanics/tribology and stress analysis/structural integrity. This paper presents an analytical model to predict quasi-static contact power losses in lubricated spur gear sets operating under the Elastohydrodynamic regime of lubrication.

In this paper, residual stress distributions in rectangular bars due to rolling or burnishing at very high rolling or burnishing loads are investigated by roll burnishing experiments and three-dimensional finite element analyses using ABAQUS. First, roll burnishing experiments on rectangular bars at two roller burnishing loads are presented. The results indicate the higher burnishing load induces lower residual stresses and the higher burnishing load does not improve fatigue lives. Next, in the corresponding finite element analyses, the roller is modeled as rigid and the roller rolls on the flat surface of the bar with a low coefficient of friction. The bar material is modeled as an elastic-plastic strain hardening material with a nonlinear kinematic hardening rule for loading and unloading.

In the wind tunnel the effect of a wind input on the aerodynamic characteristics of any road vehicle is simulated by yawing the vehicle. This represents a wind input where the wind velocity is constant with height above the ground. In reality the natural wind is a boundary layer flow and is sheared so that the wind velocity will vary with height. A CFD simulation has been conducted to compare the aerodynamic characteristics of a DrivAer model, in fastback and squareback form, subject to a crosswind flow, with and without shear. The yaw simulation has been carried out at a yaw angle of 10° and with one shear flow exponent. It is shown that the car experiences almost identical forces and moments in the two cases when the mass flow in the crosswind over the height of the car is similar. Load distributions are presented for the two cases. The implications for wind averaged drag are discussed.

The motivation for this paper is to predict the flow of water over exterior surfaces of road vehicles. We present simulations of liquid flows on solid surfaces under the influence of gravity with and without the addition of aerodynamic forces on the liquid. This is done using an implementation of a Coupled Level Set Volume of Fluid method (CLSVOF) multiphase approach implemented in the open source OpenFOAM CFD code. This is a high fidelity interface-resolving method that solves for the velocity field in both phases without restrictions on the flow regime. In the current paper the suitability of the approach to Exterior Water Management (EWM) is demonstrated using the representative test cases of a continuous liquid rivulet flowing along an inclined surface with a channel located downstream perpendicular to the oncoming flow.

Fundamental understanding of the sources of fuel-derived Unburned Hydrocarbon (UHC) emissions in heavy duty diesel engines is a key piece of knowledge that impacts engine combustion system development. Current emissions regulations for hydrocarbons can be difficult to meet in-cylinder and thus after treatment technologies such as oxidation catalysts are typically used, which can be costly. In this work, Computational Fluid Dynamics (CFD) simulations are combined with engine experiments in an effort to build an understanding of hydrocarbon sources. In the experiments, the combustion system design was varied through injector style, injector rate shape, combustion chamber geometry, and calibration, to study the impact on UHC emissions from mixing-controlled diesel combustion.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

The motivation for this paper is to consider the effect of rear end geometry on rear soiling using a representative generic SUV body. In particular the effect of varying the top slant angle is considered using both experiment and Computational Fluid Dynamics (CFD). Previous work has shown that slant angle has a significant effect on wake shape and drag and the work here extends this to investigate the effect on rear soiling. It is hoped that this work can provide an insight into the likely effect of such geometry changes on the soiling of similarly shaped road vehicles. To increase the generality of results, and to allow comparison with previously obtained aerodynamic data, a 25% scale generic SUV model is used in the Loughborough University Large Wind Tunnel. UV doped water is sprayed from a position located at the bottom of the left rear tyre to simulate the creation of spray from this tyre.

Sensor selection for the control of modern powertrains is a recognised technical challenge. The key question is which set of sensors is best suited for an effective control strategy? This paper addresses the question through probabilistic modelling and Bayesian analysis. By quantifying uncertainties in the model, the propagation of sensor information throughout the model can be observed. The specific example is an abstract model of the slip behaviour of Selective Catalytic Reduction (SCR) DeNOx aftertreatment systems. Due to the ambiguity of the sensor reading, linearization-based approaches including the Extended Kalman Filter, or the Unscented Kalman Filter are not successful in resolving this problem. The stochastic literature suggests approximating these nonlinear distributions using methods such as Markov Chain Monte Carlo (MCMC), which is able in principle to resolve bimodal or multimodal results.

Powertrain thermal encapsulation has the potential to improve fuel consumption and CO2 via heat retention. Heat retained within the powertrain after a period of engine-off, can increase the temperature of the next engine start hours after key-off. This in turn reduces inefficiencies associated with sub-optimal temperatures such as friction. The Ambient Temperature Correction Test was adopted in the current work which contains two World-wide harmonised Light duty Test Procedure (WLTP) cycles separated by a 9-hour soak period. A coupled 1D - 3D computational approach was used to capture heat retention characteristics and subsequent warm-up effects. A 1-D powertrain warm-up model was developed in GT-Suite to capture the thermal warm-up characteristics of the powertrain. The model included a temperature dependent friction model, the thermal-hydraulic characteristics of the cooling and lubrication circuits as well as parasitic losses associated with pumps.