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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.

Most OEMs are shifting their strategy and way of thinking regarding ECUs. This, in combination with the electrification of vehicles and the shift towards software-based companies (car as a device), implies one of the biggest paradigm changes in automotive history. On the other hand, despite the current struggles, remarkable advances have been made in electronic technology during the past few years. These developments have opened a door to very promising enabling technology, with exterior lighting as a main target market. These circumstances seem to have created a perfect storm leading to new strategies for electronic control and driving for (front and rear) exterior lighting. We, at our company, have investigated the enabling technology, challenges, and benefits of this emerging exterior lighting approach, that we call ‘ECU-Less’.

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.

Since several decades, passenger cars and light duty vehicles (LDV) with spark-ignited engines reach full pollutant conversion during warm up conditions; the major challenge has been represented by the cold start and warming up strategies. The focus on technology developments of exhaust after treatment systems have been done in the thermal management in order to reach the warm up conditions as soon as possible. A new challenge is now represented by the Real Driving Emission (RDE) Regulation as this bring more various, and not any longer cycle defined, cold start conditions. On the other hand, once the full conversion has been reached, it would be beneficial for many Exhaust After Treatment System (EATS) components, e.g. for overall durability if the exhaust gas temperature could be lowered. To take significant further emission steps, approaching e.g. zero emission concepts, we investigate the use of Electrical Heating Catalyst (EHC) also including pre-heating.

Two imaging techniques are used to investigate the interaction between developed combustion from earlier injections and partially oxidized fuel (POF) of a subsequent injection. The latter is visualized by using planar laser induced fluorescence (PLIF) of formaldehyde and poly-cyclic aromatic hydrocarbons. High speed imaging captures the natural luminescence (NL) of the prevailing combustion. Three different fuel injection strategies are studied. One strategy consists of two pilot injections, with modest separations after each, followed by single main and post injections. Both of the other two strategies have three pilots followed by single main and post injections. The separations after the second and third pilots are several times shorter than in the reference case (making them closely-coupled). The closely-coupled cases have more linear heat release rates (HRR) which lead to much lower combustion noise levels.

In a previous study, a passive sensor (HVAC) manikin coupled with a human thermal model was used to predict the thermal comfort of human test participants. The manikin was positioned among the test participants while they were collectively exposed to a mild transient heat up within a thermally asymmetric chamber. Ambient conditions were measured using the HVAC manikin’s distributed sensor system, which measures air velocity, air temperature, radiant heat flux, and relative humidity. These measurements were supplied as input to a human thermal model to predict thermophysiological response and subsequently thermal sensation and comfort. The model predictions were shown to accurately reproduce the group trends and the “time to comfort” at which a transition occurred from a state of thermal discomfort to comfort. In the current study, the effectiveness of using a coupled HVAC manikin-model system to evaluate a vehicle climate control system was investigated.

Passive sensor (HVAC) manikins have been developed to obtain high-resolution measurements of environmental conditions across a representative human body form. These manikins incorporate numerous sensors that measure air velocity, air temperature, radiant heat flux, and relative humidity. The effect of a vehicle’s climate control system on occupant comfort can be characterized from the data collected by an HVAC manikin. Equivalent homogeneous temperature (EHT) is often used as a first step in a cabin comfort analysis, particularly since it reduces a large data set to a single intuitive number. However, the applicability of the EHT for thermal comfort assessment is limited since it does not account for human homeostasis, i.e., that the human body actively counter-balances heat flow with the environment to maintain a constant core temperature. For this reason, a thermo-physiological human model is required to accurately simulate the body’s dynamic response to a changing environment.

Existing battery parameter model structures are evaluated by estimating model parameters on real driving data applying standard system identification methods. Models are then evaluated on the test data in terms of goodness of fit and RMSE in voltage predictions. This is different from previous battery model evaluations where a common approach is to train parameters using standardized tests, e.g. hybrid pulse-power capability (HPPC), with predetermined charge and discharge sequences. Equivalent linear circuit models of different complexity were tested and evaluated in order to identify parameter dependencies at different state of charge levels and temperatures. Models are then used to create voltage output given a current, state of charge and temperature. The average accuracy of modelling the DC bus voltage provides a model goodness of fit average higher than 90% for a single RC circuit model.

Flow visualization techniques are widely used in aerodynamics to investigate the surface trace pattern. In this experimental investigation, the surface flow pattern over the rear end of a full-scale passenger car is studied using tufts. The movement of the tufts is recorded with a DSLR still camera, which continuously takes pictures. A novel and efficient tuft image processing algorithm has been developed to extract the tuft orientations in each image. This allows the extraction of the mean tuft angle and other such statistics. From the extracted tuft angles, streamline plots are created to identify points of interest, such as saddle points as well as separation and reattachment lines. Furthermore, the information about the tuft orientation in each time step allows studying steady and unsteady flow phenomena. Hence, the tuft image processing algorithm provides more detailed information about the surface flow than the traditional tuft method.

Vehicle dynamics development relies on subjective assessments (SA), which is a resource-intensive procedure requiring both expert drivers and vehicles. Furthermore, development projects becoming shorter and more complex, and increasing demands on quality require higher efficiency. Most research in this area has focused on moving from physical to virtual testing. However, SA remains the central method. Less attention has been given to provide better tools for the SA process itself. One promising approach is to introduce computer-tablets to aid data collection, which has proven to be useful in medical studies. Simple software solutions can eliminate the need to transcribe data and generate more flexible and better maintainable questionnaires. Tablets’ technical features envision promising enhancements of SA, which also enable better correlations to objective metrics, a requirement to improve CAE evaluations.

In areas such as Active Safety, new technologies, designs (e.g. AUTOSAR) and methods are introduced at a rapid pace. To address the new demands, and also requirements on Functional Safety imposed by ISO 26262, the support for engineering methods, including tools and data management, needs to evolve as well. Generic and file-based data management tools, like spreadsheet tools, are popular in the industry due to their flexibility and legacy in the industry but provide poor control and traceability, while rigid and special-purpose tools provide structure and control of data but with limited evolvability. As organizations become agile, the need for flexible data management increases. Since products become more complex and developed in larger and distributed teams, the need for more unified, controlled, and consistent data increases.

In recent years fuel consumption of passenger vehicles has received increasing attention by customers, the automotive industry, regulatory agencies and academia. However, some areas which affect the fuel consumption have received relatively small interest. One of these areas is the total energy used for vehicle interior climate which can have a large effect on real-world fuel consumption. Although there are several methods described in the literature for analyzing fuel consumption for parts of the climate control system, especially the Air-Condition (AC) system, the total fuel consumption including the vehicle interior climate has often been ignored, both in complete vehicle testing and simulation. The purpose of this research was to develop a model that predicts the total energy use for the vehicle interior climate. To predict the total energy use the model included sub models of the passenger compartment, the air-handling unit, the AC, the engine cooling system and the engine.

Subjects who are well aware of what to judge commonly yield more consistent results in laboratory listening tests. This awareness may be raised by explicit instructions and training. However, too explicit instructions or use of only trained subjects may direct experiment results in an undesired way. An alternative is to give fairly open instructions to untrained subjects, but give the subjects a chance to get familiar with the product and context by, for example, riding a representative car under representative driving conditions before entering the laboratory. In this study, sound quality assessments of interior sounds of cars made by two groups were compared. In one group subjects were exposed to the same driving conditions that were later assessed in a laboratory listening test by taking them on a ride in one of the cars to be assessed, just before entering the laboratory. In the other group subjects made the laboratory assessments without prior car riding.

When it comes to the acoustic properties of electric cars, the powertrain noise differs dramatically compared to traditional vehicles with internal combustion engines. The low frequency firing orders, mechanical and combustion noise are exchanged with a more high frequency whining signature due to electromagnetic forces and gear meshing, lower in level but subject to annoyance. Previous studies have highlighted these differences and also investigated relevant perception criteria in terms of psycho-acoustic metrics. However, investigations of differences between different kinds of electric and hybrid electric cars are still rare. The purpose of this paper was to present the distribution of tonal components in today's hybrid/electric vehicles. More specifically, the number of prominent orders, their maximum levels and frequency separation were analyzed for the most critical driving conditions. The study is based upon measurements made on 13 electrified cars on the market.

The phenomenon of three-dimensional flow separation is and has been in the focus of many researchers. An improved understanding of the physics and the driving forces is desired to be able to improve numerical simulations and to minimize aerodynamic drag over bluff bodies. To investigate the sources of separation one wants to understand what happens at the surface when the flow starts to detach and the upwelling of the streamlines becomes strong. This observation of a flow leaving the surface could be captured by investigating the limiting streamlines and surface parameters as pressure, vorticity or the shear stress. In this paper, numerical methods are used to investigate the surface pressure and flow patterns on a sedan passenger vehicle. Observed limiting streamlines are compared to the pressure distribution and their correlation is shown. For this investigation the region behind the antenna and behind the wheel arch, are pointed out and studied in detail.

The automotive industry strives to develop high quality vehicles in a short period of time that satisfy the consumer needs and stand out in the competition. Full exploitation of simulation and Computer-Aided Engineering (CAE) tools can enable quick evaluation of different vehicle concepts and setups without the need of building physical prototypes. Addressing the aforementioned statements this paper presents a method for optimising the Electric Power-Assisted Steering (EPAS) ECU parameters employing solely CAE. The objective of the optimisation is to achieve a desired steering response. The developed process is tested on three specific steering metrics (friction feel, torque build-up and torque deadband) for two function parameters (basic steering torque and active return) of the EPAS. The optimisation method enabled all metrics to fall successfully within the target range.

It is well known that wheels are responsible for a significant amount of the total aerodynamic drag of passenger vehicles. Tyres, and mostly rims, have been the subject of research in the automotive industry for the past years, but their effect and interaction with each other and with the car exterior is still not completely understood. This paper focuses on the use of CFD to study the effects of tyre geometry (tyre profile and tyre tread) on road vehicle aerodynamics. Whenever possible, results of the numerical computations are compared with experiments. More than sixty configurations were simulated. These simulations combined different tyre profiles, treads, rim designs and spoke orientation on two car types: a sedan and a sports wagon. Two tyre geometries were obtained directly from the tyre manufacturer, while a third geometry was obtained from our database and represents a generic tyre which covers different profiles of a given tyre size.

With the increase in fuel prices and the increasingly strict environmental legislations regarding CO₂ emissions, reduction of the total energy consumption of our society becomes more important. Passenger vehicles are partly responsible for this consumption due to their strong presence in the daily life of most people. Therefore reducing the impact of cars on the environment can assist in decreasing the overall energy consumption. Even though several fields have an impact on a passenger car's performance, this paper will focus on the aerodynamic part and more specifically, the wake behind a vehicle. By definition a car is a bluff body on which the air resistance is for the most part driven by pressure drag. This is caused by the wake these bodies create. Therefore analyzing the wake characteristics behind a vehicle is crucial if one would like to reduce drag.

Automotive turbo compressors generate high frequency noise in the air intake system. This sound generation is of importance for the perceived sound quality of luxury cars and may need to be controlled by the use of silencers. The silencers usually contain resonators with slits, perforates and cavities. The purpose of the present work is to develop acoustic models for these resonators where relevant effects such as the effect of a realistic mean flow on losses and 3D effects are considered. An experimental campaign has been performed where the two-port matrices and transmission loss of sample resonators have been measured without flow and for two different mean flow speeds. Models for two resonators have been developed using 1D linear acoustic theory and a FEM code (COMSOL Multi-physics). For some resonators a separate linear 1D Matlab code has also been developed.